STEM Scholar Senior Showcase 2022

Welcome to the 2022 STEM Scholar Senior Showcase Online Exhibition!

The STEM Scholar Senior Showcase serves to recognize and celebrate our graduating class of STEM Scholars – not just for their hard work, but for their role in shaping the STEM Scholar and Honors community, and for their numerous and varied achievements both inside and outside the classroom.

We are excited to welcome the UConn community and loved ones to join us for the 2022 STEM Scholar Senior Showcase Online Exhibition. This year we are proud of the each and every one of our seniors who are sharing their Honors Thesis research and projects.

The website boasts project “pitches,” student biographies, and links to supplemental slides of each student’s Honors Thesis.

The STEM Scholar Senior Showcase is scheduled to take place in person on April 20th from 5 to 7pm in the Student Union Theater with a reception to follow on the Student Union Terrace.

Event Invitation

Program of Events

STEM Scholar Presenter Information

Neha Ande

Major: Computer Science and Engineering

Minor: Mathematics & Statistics

Student Bio: My name is Neha Ande and I am majoring in Computer Science and Engineering. Within the CSE field, I am interested in machine learning and cloud infrastructure related topics. Outside of school, I enjoy playing badminton with friends, reading books, crocheting, and drawing. After graduating, I will be working as a software engineer at Cigna.

Title of Thesis: Image Recognition Using a Siamese Neural Network

In our research group, we have been trying to make a model that easily classifies handwritten letters from the 18th century. However, we didn’t have the data set, so we have been building it from scratch for the past year and half. We realized that we need a lot of pictures for the machine learning models to accurately predict which letter is which. I decided to focus my project on trying to find a way to get decent accuracy results using the least amount of information as possible. After reading several research papers, I decided to use a Siamese Neural Network structure, which has the capability to learn information quickly with very little input. It takes two inputs and learns to find the similarities and differences between the two inputs. I only focused on the 26 lowercase letters. I formatted all the images properly for the model and built the model with parameters that are appropriate for this scenario. At first, my model was only able to accurately classify 40% of the test set. However, after lots of fine tuning, I was able to achieve a higher percentage. This type of model can be further expanded to include all 52 letters (uppercase and lowercase), digits and punctuation. This work can act as a stepping stone for converting an entire document to digit text (which is the ultimate goal in our research group).

Anusha Attre

Major: Molecular and Cell Biology

Student Bio: Anusha is studying Molecular and Cell Biology and is actively engaged within the major as the President of the Undergraduate Organization of Molecular and Cell Biology (UgO:MCB). Beginning in June 2020, she joined the Connecticut Department of Public Health in the first cohort of volunteer COVID-19 Contact Tracers, fueling her interest in public health. She additionally became a contact tracer for the University of Connecticut Storrs Campus in August 2020, and has continued applying her public health experience to shape her academic career at the university. She gained first-hand experience as a data analyst at a healthcare organization. She utilized her interdisciplinary knowledge of data analysis, public health, molecular and cell biology, and medicine to synthesize her thesis research topic. She aspires to attend medical school and support public health initiatives to make healthcare more accessible for marginalized communities.

Title of Thesis: ESKAPE Pathogens: The clinical Prevalence and Molecular Mechanisms of Antibiotic Resistance

Antibiotic and multidrug resistant pathogens are emerging rapidly in clinical settings. The ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) are the leading cause of all nosocomial, or healthcare-associated infections. The Centers for Disease Control and Prevention estimates that in the United States, more than 2.8 million antibiotic-resistant infections occur annually. The cost to treat these infections is over $4.6 billion in the United States annually. From a global public health perspective, the growing prevalence of infectious diseases is overwhelming the healthcare sector and increasing the risk of severe or deadly infections in patients. The purpose of this research study is to determine the burden of ESKAPE infections on our healthcare. Additionally, studying the molecular mechanisms of antibiotic resistance in these key high-risk pathogens will provide directions for pharmaceutical researchers to develop new antimicrobial innovations to reduce ESKAPE prevalence and improve patient outcomes.

Samantha Ballas

Major: Psychology and Allied Health Sciences

Student Bio: I am a Psychology and Allied Health Major from Easton, CT. Throughout my time at Uconn, I have been able to get involved in many organizations on campus including Community Outreach, Greek Life, and research. I am currently on the Community Outreach Board, a member of Phi Sigma Rho, and working in Dr.Treadwell's lab on my senior thesis. I also teach CPR on campus through UConn rescue. I love to read, hike and bake. One of my favorite spots near campus to hike/walk is the Mansfield Hollow Dam. After graduation, I am planning on attending medical school in the fall. I currently have an interest in primary care such as family medicine with a particular interest in working in a medically underserved or rural area.

Title of Thesis: The Importance of Health Anxiety And Emotional Reasoning to Understand Vaccine Hesitancy and Safety Behaviors: Implications for Public Health Campaigns in a COVID_19 Era

Vaccination is critical to reducing the spread of COVID-19. Therefore, in addition to the development and supply of vaccines, it is essential to maximize the willingness of individuals to obtain vaccines. However, concerning proportions of the population show vaccine hesitancy. It is critical to determine individual factors associated with this hesitancy. This study examined the impact of health anxiety and emotional reasoning on COVID-19 vaccine hesitancy and preventative behaviors. Vaccination is critical to reducing the spread of COVID-19. Therefore, in addition to the development and supply of vaccines, it is essential to maximize the willingness of individuals to obtain vaccines. However, concerning proportions of the population show vaccine hesitancy. It is critical to determine individual factors associated with this hesitancy. This study examined the impact of health anxiety and emotional reasoning on COVID-19 vaccine hesitancy and preventative behaviors. Individual factors affecting response to pandemics and public health recommendations to vaccinate include health anxiety for the current COVID-19 pandemic. This study also supported general anxiety and emotional reasoning as impacting desired vaccinations during the current pandemic. Intervention to decrease vaccine hesitancyResults can inform public health campaigns for initial vaccinations, boosters, and future pandemics to focus public health campaigns on individual characteristics of health anxiety, general anxiety, and emotional reasoning.

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Chloé Becquey

Major: Computer Science and Mathematics

Student Bio: Chloé  is from Southington, CT and is the oldest of four siblings. She has always loved solving puzzles and identifying patterns, so majoring in computer science felt like the natural choice. Once at UConn, she rediscovered her love of mathematics and working with the abstract, and declared her second major during sophomore year. She then sought out a position with the UConn Laboratory of Machine Learning and Health Informatics, with the goal of developing her skills at the intersection of math and computer science. She has been working with them since Summer 2020. Her love for problem solving has only grown these past four years, therefore she has decided that her next step is to obtain her PhD in theoretical computer science at UMass Amherst.

Title of Thesis: A Deep Learning Approach to Detecting Breast Cancer from Mammograms 

Breast cancer is the second most common malignancy in women worldwide. Early diagnosis is the key for improved survival rate. The American Cancer Society recommends annual screening for female-bodied patients aged 40 years or older. Mammography is the most commonly used modality for these annual screenings. Consequently, a sequence of mammograms is accumulated for each patient, and radiologists can contrast the images taken at successive years to detect changes. In this thesis work, we propose to use deep learning methods to help analyze pairs of mammograms from these sequences and then segment the tumor if one exists.
Detecting the tumor is not as simple as a pixel-by-pixel subtraction, as natural differences in the tissue can occur. Instead, we encode both images, essentially taking the over 500,000 pixels that represent the mammogram and turning them into a set of 5,000 numbers. This is where deep-learning comes into play, as the network needs to figure out the best encoding.
How do we segment the tumor from this? The idea is to take the difference between the encoded forms of the current and previous image. Similar mammograms - ones where both images in the pair do not have a tumor - should have similar representations. Thus, if a major difference is detected between the encoded mammograms, that difference likely represents something that wasn’t there before: the pixels that represent the tumor.

Serena Beri

Major: Neuroscience and Psychological Sciences

Student Bio: I am a current Undergraduate student at the University of Connecticut, obtaining a B.S in Biological Sciences and minors in Neuroscience and Psychological Sciences. A member of the Honors Program and BOLD Women’s Leadership Network. For my senior thesis, I conducted research for “Protective Mechanism of Caffeine on Microglia in Preterm Hypoxic Ischemic Injury” which focuses on assessing how caffeine is an effective neuroprotectant against Hypoxia Ischemia in Preterms due to its reduced microglial activation affects. As part of the BOLD program I conducted a service project on “Addressing the Gap of Women in Stem Professions” to address the disconnect that occurs between women graduating with STEM degrees and those who actually enter a STEM career by connecting young women together and showing them that the opportunities are endless. After my time at UConn, I hope to work in the healthcare field and promote representation in STEM.

Title of Thesis: Protective Mechanism of Caffeine on Microglia in Preterm Hypoxic Ischemic Injury

This study investigated the neuroprotective effects of caffeine HI treatment on microglia in rodent models. Hypoxia Ischemia (HI) is an especially damaging injury in preterm infants as it leads to 23% of neonatal deaths worldwide. HI has been categorized as a brain dysfunction that occurs when low oxygen blood levels prevent the brain from receiving enough blood supply. This results in nerve cell death, as the neuronal ion gradients and energy demands are not met. Once these neurons die they cannot regrow, resulting in a large number of learning disabilities and harmful cognitive effects such as cerebral palsy, epilepsy, ADHD, and even death. Therefore, it is necessary to study protectants that can be used to treat HI. The subjects used were 29 male and female rats, where rats were separated into four conditions: SHAM saline, SHAM caffeine, HI saline, and HI caffeine. Conditions were also separated based on sex, to observe sex differences in microglial activation. Since previous research shows male animals have improved HI outcomes when treated with caffeine and caffeine reduces microglial over activation, it was hypothesized that the male HI caffeine group would have the lower microglial area and larger DAPI density. The results supported this hypothesis, as the caffeine group had the lower soma area therefore they had reduced microglial activity. Applications of this study will provide valuable insights in developing a drug therapy technique that can be used to prevent nerve cell death. This technique will be influential in treating preterm infants suffering from Hypoxia Ischemia or other neuropathies.

Jessica Berry

Major: Nursing

Student Bio: I will be graduating in May with a BSN from the UCONN School of Nursing. I've greatly enjoyed my time at UCONN and the opportunities the STEM Scholar Program has provided me with and I'm excited to be graduating. I hope to start my career as a Registered Nurse after graduation. People have always inspired me which has been my motivating factor in deciding to pursue nursing. I hope to become a pediatric operating room nurse post graduation.

Title of Thesis: Maternal Perceptions Regarding Care of their Infants with Neonatal Abstinence Syndrome

This project explores the experiences mothers had when interacting with healthcare members whilst receiving care for their infant diagnosed with Neonatal Abstinence Syndrome (NAS). This is important because oftentimes moms whose newborns require care for NAS may suffer from opioid use disorder. Frequently, the use of opioids by pregnant mothers is looked at as being a choice rather than an illness these women are suffering from.
Data was collected for this study using a quantitative descriptive study format. Surveys were distributed to new moms with infants diagnosed with Neonatal Abstinence Syndrome and the moms were asked some questions about their interaction with healthcare. These surveys consisted of five questions including “How do you feel you were treated?” and “How do you feel your baby was treated?”. It was found that mothers will face judgment and have a feeling of not being understood by healthcare staff. It was also found most moms were trying their best to be good moms given the circumstances and they expressed their lack of education on NAS.
Moving forward with this knowledge further research can be conducted to see how these interactions might be improved in the future. As nurses it is important to be aware of personal biases so that they do not encroach on the care we are providing to our patients and their families and this research highlights an area that needs improvement. It’s important to keep in mind that care for this population can result in more family centered care in future healthcare interactions.

Akash Binoj

Major: Computer Science and Mechanical Engineering

Minor: Mathematics

Student Bio: My name is Akash Binoj and I’m from West Hartford, CT. I am a graduating senior studying a double major in Computer Science and Mechanical Engineering with a minor in Mathematics. While that sounds like a lot, my passion is in robotics and having the overlap between the two fields has helped prepare me for many projects I’ve worked on and hoping to work on in the future. Throughout my UConn career, I’ve researched for two different CS Research Labs, one involving path optimization and the other in an independent study on an autonomous drone. For professional experience, I’ve completed two internships as a Software Engineer with Medtronic, working on surgical robotics, and one with Tesla, working on the prototype Tesla SemiTruck. In my free time, I take part on the executive board for the Indian Students Association and DJing for bars in Storrs on the weekends!

Title of Thesis: CloudBots: Autonomous Atmospheric Explorers 

The CloudBot is an autonomous weather balloon that operates on the principle of variable buoyancy to move in the atmosphere. This project aims to develop a device that can collect atmospheric measurements and communicate them with the goal of reducing reaction times to detrimental natural weather disasters. CloudBot consists of a helium-filled balloon, the robotic payload, and an air cell, with variable pressure to allow the device to ascend or descend based on a flight plan or manual control.
To achieve the goal to build a controllable weather balloon, the principle of variable buoyancy was used. An air system directs the flow of air through the robot, and is designed around a 12V DC compressor pump, and two solenoid valves. Transceivers on both the CloudBot and the ground allow instructions to be transmitted to an on-board Arduino which then controls the valves and the pump accordingly. A standard weather balloon with a maximum diameter of 20 feet contains the Helium that provides the buoyancy force for the CloudBot, but it will be inflated to roughly a six-foot diameter. Variable buoyancy is made possible by a developed air cell. By pressurizing this air cell, it provides just enough weight to overcome the upward buoyancy force of the Helium. This project goes over the build process and the complex communication protocol required to maintain contact with the balloon for measurements and to operate the pump and valves to have the device ascend or descend.

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Ling Chi

Major: Biomedical Engineering

Minor: Mathematics

Student Bio: Hi! I’m Ling, and I’m from Wethersfield, CT. I am majoring in Biomedical Engineering with a concentration in Computational and Systems Biology. On campus, I am the Operations Manager of WHUS Radio, the student radio station, where I handle our finances and help supervise the staff to put on various events and programs. I am also involved with the UConn Health Leaders as a research coordinator, where we work with volunteers to address social determinants of health in clinical settings. I am currently working on an IDEA Grant research project in medical informatics and social determinants of health, and I plan to continue to conduct research in this field after graduation! I hope that in my career, I can use my undergraduate experience in engineering to design solutions to improve patient outcomes in medicine. Outside of school and work, I enjoy traveling with my family, trying new foods, and cooking with my friends!

Title of Thesis: Device and Mobile App Development for Retinal Diagnosis 

Consistent retinal imaging is an important aspect of preventing many eye diseases like diabetic retinopathy, which can often lead to blindness. However, access to medical professionals, as well as the expensive equipment typically used in imaging, is limited in low-income areas. This is reflected in the high percentage (about 90%) of visually impaired people that live in low- income countries. In this project, we aimed to build a low cost, easily accessible smartphone-based device that can capture a retinal image and diagnose it for diabetic retinopathy and other ocular diseases. Our goal was to develop a retinal imaging method that doesn’t require a medical professional present to support the screening and prevention of eye diseases in low- income areas with limited healthcare access.

This design has both a hardware aspect and a software aspect. On the hardware side, we developed a 3D-printed smartphone adapter that includes a 20D ophthalmic lens, fiber optic cable, and an optional silica beam splitter. The adapter connects the smartphone flashlight to the fiber optic cable, which is used to illuminate the retina for imaging. The ophthalmic lens is used to focus and magnify the image. All components can be found off-the-shelf or are 3D printed. On the software side, we developed an app, compatible with Android devices, that uses a machine learning model to classify a retinal image for diabetic retinopathy, glaucoma, or macular edema. Images can either be captured within the app or uploaded from the phone’s camera roll.

Andrew Christenson

Major: Mechanical Engineering

Student Bio: My passion has always been finding ways to combine sports and engineering. Some of my most enjoyable experiences have been engaging in interdisciplinary research with the Korey Stringer Institute and the Institute for Sports Medicine. I have spent lots of time researching head impact kinematics in soccer and hope to transition to more equipment-based research in graduate school. The end goal is to utilize engineering as a tool to improve the safety and performance of athletes of all ages.

Title of Thesis: Utilizing Computational and Experimental Methods to Evaluate the Biomechanics of Heading in Soccer 

Soccer is one of the most popular sports in the world. While most concussions in soccer are due to head-to-head collisions, there has been growing concern over the risks associated with purposeful heading of the soccer ball. Some evidence suggests that engaging in headers may result in sub-concussive impacts that can lead to negative short-term and long-term neurological sequelae. An alternative approach to the age restrictions put in place by the United States Soccer Federation in an attempt to mitigate head injuries is to ensure mean head acceleration from a header is reduced with minimal rule changes. The computational portion of my project presents a dynamic model of a player heading a soccer ball to examine the general relationship between ball pressure and mean head acceleration toward the purpose of motivating a more complex and comprehensive analysis of heading in soccer. On the other hand, there is limited research observing the relationship between header technique and head kinematics. The experimental portion of my project aims to investigate the influence of header technique on head kinematics by utilizing 3D motion capture to quantify elements of an athlete’s form.

Cameron Cianci

Major: Physics and Computer Science Engineering

Minor: Mathematics

Student Bio: I am a UConn honors Physics and Computer Science Engineering major. I'm incredibly passionate about designing quantum technologies such as quantum computers or quantum sensors. My love for physics started in middle school and I'm grateful that I have been able to pursue it through my degree and my work, and I hope to continue my studies of it when I apply for graduate school this fall. In my junior year, I was a part of Professor Ilya Sochnikov's lab in superconducting physics and SQUID microscopy at UConn. That summer I was accepted into a summer research program in the University of Texas Rio Grande Valley in nanophononics. When I returned, I joined research in QCD with Professors Luchang Jin and Thomas Blum here at UConn. I've attended many graduate level courses including Many Body Quantum Field Theory, General Relativity, and Machine Learning. In addition to my academics I also love to rock climb, sail, and hike mountains in my free time.

Title of Thesis: Lattice Chiral Effective Theory

My research is done in Quantum Chromodynamics, which is the study of how nuclei work. This usually involves working with a quantum field known as the strong force or gluons, and the matter which it affects which is called quarks. This mathematical theory is very difficult to solve and so instead QCD researchers usually end up making it easier by putting the theory in a box, also known as a lattice, where we can find approximate solutions to our mathematical problems instead of exact solutions. There is an alternative to this approach that works at low energies called Chiral Effective theory, it basically forgets about the smaller particles of the theory and only remembers these particles called pions. This effective theory has an advantage at low energies because it has an additional way to solve it by using something called perturbation theory, which is shown in the image above and is very well studied in physics. My research with Professor Luchang Jin and Thomas Blum examines Chiral Effective Theory, both by putting it in a box also known as a lattice, and through the well studied method of perturbation theory. This combination allows for us to compare and contrast the predictions of both of these methods, such as the prediction of pion scattering, or how two particles bounce off each other. Since I am graduating this fall, this research is still in progress, and we will continue to run many lattice simulations over the next few months to collect data, and compare the two methods.

Mansi Dhond

Major: Management and Engineering for Manufacturing

Student Bio: Mansi, from Greenwich, CT, is pursuing a combined engineering and business B.S. in Management and Engineering for Manufacturing. On-campus, she is Materials Director of Global Health Spaces on Campus, where she has helped host annual global health Hackathons and Symposiums. She has been recognized as a UN Foundation Global Health Fellow and is a recipient of the IDEA Grant and Change Co-op Legacy fellowship. Mansi is also passionate about preserving and promoting the Indian classical arts, serving as Co-President of Sanskriti, UConn’s Indian classical arts collective. Outside of UConn, she is an avid semi-professional painter and graphic designer. She is enthusiastic about traveling, rock climbing, and diving with marine life. Her favorite part of college has been exploring connections between seemingly unrelated topics. She aspires to use her background in engineering, business, art and global health to innovate interdisciplinary and sustainable solutions to pressing contemporary problems.

Title of Thesis: A Novel Combination of Seaweed Farming and Aquaculture to Maximize Carbon Sequestration and Promote Food Sustainability 

In order to reverse climate change, it is not enough to simply reduce emissions; it is necessary to find solutions which sequester carbon to offset the emissions produced from human, industrial, and agricultural activities. Carbon dioxide removal refers to the process of removing CO2 from the atmosphere. Since this is the opposite of emissions, technologies or practices that remove CO2 can be described as achieving 'negative emissions'. Food sustainability is also a major present day challenge as environmental change and habitat degradation have threatened the food supply of communities across the world. Furthermore, seafood and overfishing have had adverse effects on the aquatic biome. The production of seafood or through aquaculture in combination with seaweed farming also allows for the operation to be profitable and sustainable. This thesis presents a technical, financial, and environmental analysis analysis and overview of a concept pilot operation combining seaweed farming with aquaculture.

Aditi Dubey

Major: Computer Science and Engineering

Minor: Mathematics

Student Bio: Aditi is from Danbury, Connecticut is pursuing a B.S.E in Computer Science and Engineering with a minor in Mathematics. She is an active officer in the Women in Computer Science organization to aid in focusing on supporting women in their academic, professional and personal pursuits. On-campus she is also involved with programs in the Werth Institute which promotes her passions for innovation and entrepreneurship. Outside of academics, Aditi enjoys playing the piano, acrylic painting, and hiking. After graduation, she is planning to work as a software developer, and pursue a Master's in Computer Science.

Title of Thesis: Predicting The Political Polarity Of Twitters Regarding Vaccine Passports

I am presenting a system for detection through a natural language processing project for a multi-classification problem which is classifying the political leaning of tweeters on the topic of Covid-19 Vaccine Passports. With the authorization and release of numerous COVID vaccines, there was a mass uproar on social media regarding the potency and legitimacy of the vaccines. Subsequently, many discussions and debates occurred over the support and opposition of the vaccine passports. Using Machine Learning Classifiers this project will predict the political polarity of a Twitter user to determine if they are a Democrat vs. Republican vs. Libertarian. Data preparation and labeling will be done to ensure that the dataset is cleaned and pre-processed such that it focuses on tweets that refer specifically to key words like “vaccine passport” and columns with respect to the political leaning of the Tweeter. The dialogue of the textual tweets will then be classified through feature extraction methods for the purpose of starting with the initial data set and then building values that are informative and nonredundant to give a linear combination of the existing features. This will ultimately have fewer features that can capture the same information for a large set of data to increase the accuracy of the learned models that will be implemented. Finally, this research will be judged based on the accuracy and precision obtained from the classifiers and neural networks implemented.

Aditya Dubey

Major: Computer Science and Engineering

Minor: Mathematics and Electronics & Systems

Student Bio: My name is Aditya Dubey and I am Computer Science and Engineering major, with minors in Mathematics and Electronics & Systems, at UCONN. I have a profound interest in Artificial Intelligence, Machine Learning, Robotics, IoT, Augmented Reality, and Web/Mobile development. I am very passionate about these fields and using computer science for innovation. On-campus, I am the founder and director of Husky Developers (A student-run organization where individuals from all backgrounds can learn modern technologies through involved workshops and project teams). In my free time, I enjoy playing basketball, and soccer, trying our new cuisines, traveling, and developing apps. After graduating from UCONN, I plan on starting my career as a software engineer in the tech industry and also plan to pursue a Masters's degree.

Title of Thesis: A Machine Learning and Deep Learning Framework for Binary, Ternary, and Multiclass Emotion Classification of Covid-19 Vaccine-Related Tweets

My research mines public emotion towards the Covid-19 vaccine based on Twitter data collected over the past 6-12 months. This project is centered around building and developing machine learning and deep learning models to perform natural language processing of short-form text, which in our case tweets. These tweets are all vaccine-related tweets and the goal of the classification task is for our models to accurately classify a tweet into one of four emotion groups: Apprehension/Anticipation, Sadness/Anger/Frustration, Joy/Humor/Sarcasm, and Gratitude/Relief. Given this data and the goal of the paper, we aim to answer the following questions: (1) Can a framework be developed for machine learning and deep learning multiclass classification models to accurately infer one of four listed emotion groups represented by a vaccine-related tweet? A follow-up to this question is: Can we improve the overall model performance by clustering the emotions into a ternary classification problem? (2) Is there a significant binary distinction that can be made between tweets that express “negative” emotions (Apprehension, Anticipation, Sadness, Anger, and Frustration) and “positive” emotions (Joy, Humor, Sarcasm, Gratitude, and Relief)? This research will present a framework that takes in the raw tweet data and through a pipeline that applies data preprocessing, feature extraction, data splitting & sampling, and ultimately emotion classification. Through these questions, the aim is not only to determine the overall acceptance and sentiment of the vaccines by the public but also to understand the steps public health officials can take to further educate hesitant and/or fearful citizens while also incentivizing it.

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Sabaa Fayazi

Major: Physiology and Neurobiology

Student Bio: Sabaa is a graduating senior and Stem Scholar from North Brunswick, NJ completing her degree in Physiology and Neurobiology. After graduation, she plans on working towards her master's in Global Development from Harvard University as well as working as a scribe and medical assistant in the neurology department of RWJ Barnabas Health. She plans on attending medical school and specializing in surgery while also working as an advocate for healthcare policy that enhances patient care.

Title of Thesis: Neurophysiology of Sleep

Oscillations in neuronal activity are one of the defining characteristics of the sleep cycle that regulates so many important biological functions such as memory consolidation, growth factor release as well as stress hormone management. So much of daily functioning is determined by this cycle, yet there are not many papers that outline the current understanding of the localization of these signals or their physiological characteristics. The goal of this paper is to take an in-depth look into current research about neuronal activity in sleep, mainly sleep spindle and slow-wave activity, and summarize what is known about their localization and burst pattern as well as how these factors relate to specific sleep-related movement disorders (SRMD) and parasomnias.

Jennifer Field

Major: Biomedical Engineering

Student Bio: Hello! I’m Jenny, a graduating senior in the school of biomedical engineering. In my free time I can typically be found playing or watching sports, making custom crafts for my small business, or taking a nap. While at UConn I participated in intramural sports, Huskython, and was the president of a club called Confetti for Kids. I’ve loved my time at UConn being a TA and peer mentor for the school of engineering. Due to COVID, I only had 2 semesters of complete normalcy, so my time at UConn has definitely flown by. After graduation, I’ll be moving to Massachusetts to work as a Validation and Integration Engineer on Patient Monitoring systems at Draeger Medical. I’m proud to be a Husky! Woof!

Title of Thesis: A Human Factors Approach to the Optimization of Prostheses for K3 and K4 Amputees

Paralympic athletes serve as pillars of hope for the 20% of Americans with disabilities and as a marvel of human spirit and ingenuity. Sport specific prostheses are essential to provide these athletes with the functionality necessary to compete and should be optimized for safety and performance. Unfortunately, barriers such as cost and accessibility make it difficult to obtain the necessary devices for the level of performance required. The purpose of this design project is to fabricate a part that can be attached to a K4 prosthesis to convert its functionality to that of a K3 prosthesis. Essentially, an individual would be able to add or remove this part to allow the switch between running, walking, or hiking modalities. Ideally para-athletes would exhibit biomechanically identical movements when compared to a typical athlete. Interviews with amputees will inform ergonomic aspects of the design including comfort and the level of technicality that can be reached before the device is too complicated to use. 3D Motion Capture as well as force platform data will focus on rollover shape testing to compare the center of pressure for the prosthesis in both the K3 and K4 modes to a non-amputee. The result of this project provides beneficial information to prostheses manufacturers and production teams by introducing an alternative hybrid device design, and will work to mitigate the barriers of cost and accessibility as a user will only need to obtain one device instead of two.

Reinier A. González Heredia

Major: Molecular and Cell Biology

Minor: Global Studies

Student Bio: A Molecular and Cell Biology Major with a minor in Global Studies, Reinier has served as the program coordinator for volunteer programs at UConn Health and has been involved with cancer immunotherapy research in UConn’s Pharmacy Department. He is currently serving as the STEM Scholar Executive Director and is a Student Leader in the Louis Stokes Alliance for Minority Participation (LSAMP). Additionally, Reinier is one of the Honor's Program Guide for Peer Success (GPS), in which he helps other Honors students navigate their requirements and extracurricular involvement. In the future, Reinier hopes to work with an organization such as Doctors Without Borders, inspired by his previous experience working alongside medical personnel in response to Hurricane Maria in Puerto Rico.

Title of Thesis: Structure, Regulation and Function of VISTA as a novel immunotherapy ligand 

Immunotherapy for cancer treatment entails using and bolstering the pre-existing defense mechanisms present in the human body to fight cancer. In the immune system T cells are focused on protecting the human body from pathogens and clearly mutated cells through specific T cell receptors (TCRs). Cancer immunotherapy seeks to increase the antitumor efficacy of these T cells by therapy with immune checkpoint inhibitors or expanding adaptive immunity through the transplant of genetically engineered T cells. Knowing this, the primary goal of my research is to utilize directional cloning to uncover potential immunotherapy ligands. VI-domain Ig suppressor of T cell activation (VISTA) functions as an inhibitory immune- checkpoint protein. . VISTA blockades have shown to be a promising notion of study as it has shown to improve antitumor T- cell responses, leading to impeded tumor growth and improved survival. To uncover and further understand these potential immunotherapy ligands directional cloning is implemented. Directional cloning contains various steps all crucial for the eventual DNA analysis of the end transformation, to be used to create cultures of the vector with desired target insert. During my time at the lab I implemented PCR, Gel Electrophoresis, Restriction Digest, Transformation and creation of colonies, glycerol stock creation, DNA sequencing, and QuickChange mutation to further study VISTA.

Tawana Gray

Major: Nursing

Student Bio: I am a graduating senior nursing student, STEM Scholar, and Urban Service Track/AHEC Scholar at the University of Connecticut. I was originally born in Jamaica, but immigrated to the United States in 2010. My honors thesis focuses on examining the prevalence of persons experiencing homelessness with diabetes utilizing an urban medical respite program. I am interested in helping others and utilize my time by participating in different programs that allow me to broaden my knowledge. After graduation, I plan to further my education while continuing to serve the community and contribute towards the goal of reducing health disparities.

Title of Thesis: Diabetic persons experiencing homelessness admitted to a medical respite program

Homelessness and diabetes are two complex public health issues that often intersect and affect the lives of many individuals. Diabetics experiencing homelessness have many health care challenges and are often frequent users of emergency departments and also have a higher risk of readmission after hospitalization. After visiting a homeless shelter I learned of a medical respite program in New Haven for hospitalized persons experiencing homeless. A medical respite is for those who are considered medically safe to be discharged from a hospital, but require more time to properly heal before going back to their living conditions. Curious, I wanted to learn how many diabetics used this program. I contacted Michael Ferry, a social worker at Yale New Haven Hospital who was involved in the program and has helped me access five years of patient data for my research. I also reached out to an epidemiologist, Dr. Brian Maguire, to further help with analyzing the data provided. The aim of my research was to determine the prevalence of persons experiencing homelessness with type 1 and type 2 diabetes utilizing the Columbus House Medical Respite Program in New Haven after discharge from Yale New Haven Hospital. My research found that this respite service is well utilized by this population. Examining the patient population of those admitted into this program can open conversations, contribute to the literature, and work on providing targeted interventions that considers the unique challenges of diabetics experiencing homelessness.

Bhavana Gunda

Major: Physiology & Neurobiology & Global Health

Student Bio: Bhavana Gunda is a senior pre-medical student in the College of Liberal Arts and Sciences pursuing a dual degree in Physiology & Neurobiology and Global Health. At the University of Connecticut, she is part of HuskyTHON’s Management Team and on the Executive Boards of Global Health Spaces on Campus as the Panel Coordinator and Medical Minds Matter as the Program Coordinator. She also does research with the Kanadia lab in the Physiology & Neurobiology department, studying processes involved with minor intron splicing. In her free time, Bhavana likes to spend time with friends, read, go on hikes, and travel. In the fall, Bhavana will be attending UConn School of Medicine in Farmington, CT.

Title of Thesis: Investigating the Role of SNRNP70 in the Splicing and Expression of Minor Intron-Containing Genes 

For this project, the Kanadia lab is impairing spliceosome function using small interfering RNA targeted against a component of the major spliceosome, the U1-70k protein responsible for recognition of the 5’ splice site at the exon-intron border. In minor intron-containing genes (MIGs), the major and minor spliceosomes interact at these junctions, where adjacent introns that are initially recognized at splice sites are paired across exons. This exon-definition model of splicing requires coordination of spliceosomal complexes that is mediated by protein-protein interactions, including those of U1-70K.

For my thesis project, I am processing RNA extracts into cDNA that is used in qPCR analysis to confirm and quantify the knockdown. Using these samples, I am also qualifying expression and alternative splicing patterns in MIGs known to be differentially expressed in response to minor snRNP knockdowns. This data will help to contextualize the molecular mechanisms of splicing around minor introns and answer questions about how splicing machinery interacts with other parts of the machinery, how it interacts with pre-mRNA, and the extent to which the U1-70K protein is involved in the cross-talk between the two machineries. Understanding the splicing pattern of MIGs is important because many of these genes have functions important for viability and proper development. For example, the gene NUP210 is a protein-coding gene for the nuclear pore complex in eukaryotic cells and the gene VPS11 is involved in vesicle trafficking in the endosome/lysosome pathway. MIGs are important for many cellular functions to occur, such as cell cycle, and are implicated in developmental defects like microcephaly, cancer, and limb development.

Qingli Hu

Major: Physiology & Neurobiology, Psychology

Student Bio: Hi! My name is Qingli, and I'm sad to graduate this spring and leave Storrs. During my time here, I've been involved with several different organizations (besides STEM Scholars, for which I am the Community Engagement Chair), including Community Outreach, the Alzheimer's Association, Student Health and Wellness, research in the Markus lab and Bellizzi lab, Badminton team, Nu Rho Psi, Undergraduate lab TA, PATH, etc. In my free time, I enjoy watching YouTube shorts and playing badminton. My plan for after graduation will be attending UConn Health in Farmington as an MD candidate, and I'm especially interested in neurology.

Title of Thesis: Case Study: Effects of Ultrasonic Vocalizations on Rat Behavior and Place Cell Remapping in the Hippocampus

My project investigates the connection between auditory stimuli with place cell remapping in the hippocampus, which is the phenomenon of changes in neuronal firing patterns, occurring as the environment around us changes and updates. This idea stems from a book that I read called The Man Who Mistook His Wife For A Hat by Oliver Sacks, which contained record of several patients who were able to compensate for symptoms of severe neurodegenerative diseases using other sensory input, especially music. From a personal anecdotal standpoint, there are certain songs or sounds that sometimes trigger vivid flashbulb memories. This was amazing to me, and because of this curiosity with sound and the current behavioral neuroscience research with which I am helping in the Markus lab, I proposed to add my own twist on the single-unit recording experiment on the linear maze with the component of an auditory stimuli. I read that rats emit ultrasonic vocalizations at mostly 22 and 50 kHz as an emotional response, so playing these sounds while recording from rats’ hippocampal neurons will allow us to determine if remapping can be induced. Occurrence of remapping would suggest that the emotional state under which location information encountered can affect the way that it is encoded. Investigating normal physiological functioning of memory encoding will help us understand malfunctions in the system and corresponding treatment options for neurological disease states.

Nina Huczko

Major: Chemical Engineering and French Studies

Student Bio: Hi! My name is Nina Huczko, and I am a senior studying Chemical Engineering and French. Throughout my time here at UConn I’ve loved being involved all over campus including in undergraduate research, student organizations, and outreach. Through my research, I have had the pleasure of working with Professor Luyi Sun and his graduate student Kuangyu Shen on their thin-film project, which I expanded to write my honors thesis. Additionally, I have been a member of Engineering Ambassadors, a student-led engineering outreach organization, since my first semester at UConn. Since then I served as president for the past two years. I also loved being involved in HuskyTHON, an 18-hour dance marathon benefitting Connecticut Children’s Medical Center. My fundraising efforts over my four years here total to over $3,500 for the kids. My future plans are to complete an internship with Eastman Chemical Company this summer before moving to Toulouse, France in the fall to finish my French degree.

Title of Thesis: Multi-Layered Stimuli-Responsive Dynamic Shape Change Device

Inspired by the natural adaptability of the chameleon, we proposed a multi-responsive film-substrate structured shape-change device. Specifically, our device had three layers: the first is a shape-change film, the second is a Liquid Crystal film, and the final is a polymer substrate. The elasticity of the device is controlled by varying the cross-linking ratio of the polymer. The device demonstrates multi-stimuli responsiveness which can be activated by moisture, light, and electro-mechanical modes. This is enabled by the unique properties within each layer. For example, the shape-change layer enables the moisture and light stimuli responses by exhibiting volumetric changes as a result of moisture gain or loss. This enables the bending response of the device. The middle Liquid Crystal layer makes the device thermally responsive with temperature ranges corresponding to a specific color. The device demonstrates excellent reversibility and durability leading to many potential applications. One of these applications is in soft robotics which is the design and construction of flexible-bodied robots.

Nailah Hutchinson

Major: Individualized Major: Data Science, Computer Science

Minor: Analytics

Student Bio: My name is Nailah Hutchinson, I am a senior Data Science major, which is an Individualized Major here at UConn. I originally started my journey here at UConn as a biological sciences major but soon learned that it was not the major for me. I then learned about the Individualized Major program which allowed me to build my own major combining my favorite subjects: math, statistics, and computer science. Aside from academics, I have been a Residential Assistant for the Buckley Shippee community (first year honors housing) for the past three years.
I am from Hamden, CT where I live with my parents, sisters, and dog Magnus. I love listening to music, reading a good book, and watching tv. After graduating I will be working as a Data Lake Engineer for Synchrony Financial as a part of their Technology Business Leadership Program.

Title of Thesis: Modeling Tools for NBA Data: An Analysis of Certain Measures to Determine a NBA Team’s Overall Performance 

Basketball is a beloved sport watched by millions of people worldwide. In the NBA everything is documented. Whether it is a free throw, player injury, or minutes played, statistics from every game are recorded. The data collected can be used to create different types of models which look at a variety of factors. This project will look at how certain statistics, such as the number of players playing in a game and home advantage, determine the ultimate measure of a team’s performance: a win or a loss. In order to determine whether or not a team won, a predictive model was to be created. To begin the process of developing a model, the data was downloaded from, a data science and machine learning community. The NBA data includes the following data tables: games, games details, players, and more. Each data table holds thousands of rows of data that could be analyzed. The data was then imported into SAS and was then cleaned and processed (outliers were removed, data reorganized to fit the needs of the project, variables were created, etc.). For example, the raw data did not include average team statistics from prior games so this had to be calculated by creating new calculated fields. A logistic regression model, a type of predictive model, was then created and fine-tuned for accuracy.

Chris John

Major: Mechanical Engineering

Student Bio: Good day! My name is Chris John, and I will be graduating with a degree in Mechanical Engineering. I occasionally enjoy throwing myself into the unknown like the time I studied abroad in Singapore (applying days before the deadline), flew a small plane a couple times, joined the Irish Hurling team at UConn, or decided to go into undergraduate research leading to post- graduate studies. I enjoy biking, travelling around, and just seeing what is out there.

Title of Thesis: Triggering Thermal Runaway in Lithium-ion Batteries 

A world without lithium-ion batteries seems unimaginable. Batteries allow mobile devices ranging from phones, to laptops, and now all-electric vehicles to function. However, a latent danger known as thermal runaway exists in these batteries. Damage to the battery, overcharging, or excessive heat can trigger a series of decomposition reactions, releasing heat and further increasing the rate of these reactions until this released heat triggers a fire engulfing the battery. While experimental designs exist for evaluating thermal runaway, significant safety hazards and impracticality may impede testing efforts. Finite element analysis, therefore, becomes a vital tool in modeling thermal runaway and mitigation techniques. However, there is limited literature regarding modeling and evaluating thermal runaway in generalized models subject to different conditions and materials. This project saw the creation of a computational model which can induce thermal runaway in a single battery, providing insight to temperatures reached and heat generated. A generalized battery case was then designed and modeled to hold multiple batteries with one cell forced to undergo thermal runaway. The case material, dimensions, and other conditions were varied to determine effective methods to prevent thermal runaway from spreading to other cells.

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Lavar Johnson

Major: Allied Health Sciences with a concentration in Public Health and Health Promotion

Minor: Psychological Sciences

Student Bio: I am an Allied Health Sciences Major at the University of Connecticut. I joined the CAHNR Nutrition Team as a part of the McNair Fellows program in Fall 2020, with my research continuing now as a McNair and LSAMP Scholar. I am currently working alongside Dr. Valerie Duffy to investigate the feasibility of serious gaming on health promotion among tweens and teens. My research involves various aspects of game design and development. My current research project the Eat and Move as I Like Nutritional Game (EAMAIL), Uses serious gaming to transmit health information in educational settings. EAMAIL aims to increase knowledge about MyPlate food groups and less healthy sweets, increase self-awareness of eating, and motivate healthier diets and physical activity in full story and free play modes. The aim of my thesis is to develop and pilot-test an evaluation framework for EAMAIL in a classroom setting to promote engagement and self-awareness of eating as well as motivate healthier diet behaviors in tweens/teens.

Title of Thesis: Feasibility and Usefulness of Evidence-Based Gaming to Deliver Health Messages to Tweens in a Classroom Setting

The aim of my thesis was to assess if a web-based nutrition education game, Eat and Move as I Like (EAMAIL), encourages children and adolescents to think about healthy eating and motivates them to eat healthier. Our interdisciplinary team developed the EAMAIL web-based game to be fun and challenging for tweens and young teens. The game provides information about MyPlate food groups and less healthy sweets, promotes self-awareness of eating, and provides messages to motivate healthier diets and physical activity in full story and free play modes. During gameplay, children rate their liking/disliking of MyPlate food groups (i.e., self-awareness), liking/disliking to try diet improvements aligned with motivational message, and, at the end of the game, desire to play the game again and if the game made them want to eat better. I helped refine in-game messages, standardized the game offering in an educational setting, and developed the game evaluation informed by the Design, Play, and Experience framework for serious games for IRB-approval and sharing with school stakeholders. My analysis of game play in IRB-approved nutrition education sessions provides support that the game is feasible in a single classroom setting, is fun for children, while increasing their willingness to eat healthier. Thus, EAMAIL appears a novel tool for motivating healthier diets in children in a fun and interactive manner. Fueled by these preliminary findings, we are working to offer EAMAIL in waiting rooms of healthcare settings to focus children’s attention on healthy eating prior to an encounter with a clinician.

Mitchell Johnson

Major: Electrical Engineering

Minor: Computer Science & Mathematics

Student Bio: My name is Mitchell Johnson, and I am an Electrical Engineering major. I grew up and currently live in Glastonbury, Connecticut. At UConn I am the president of Electric Motorsports, a club whose goal is to design and build an electric racecar. I am also a part of the Club Sailing Team and Beta Theta Pi Fraternity. In my free time, I enjoy hanging out with friends and spending time outdoors. I like spending time fishing, hiking, and playing baseball, basketball, or golf. Throughout college, I have had an internship at Unholtz-Dickie Corp, participated in a power engineering summer research program, and had an internship at Collins Aerospace. After I graduate, I will continue to work at Collins Aerospace as an Associate Electrical Design Engineer.

Title of Thesis: Smart, Efficient and Light Solar Microgrid Inverter

With the rise of the use of renewable energy to mitigate the effects of climate change, many new solar panels are being added to the electrical grid. In order to properly connect the solar panels to the grid, a solar inverter is needed. This device takes the electrical power that the solar panels produce (which is DC power) and transforms it into AC power, which is what the electrical grid uses. The inverter also actively manages the output of the inverter to make sure it agrees with the grid voltage. My project, which I completed with my senior design group, was to design and build a microgrid inverter for the International Future Energy Competition. The goal was to make an inverter that had robust grid control, including safety measures, as well as making it as light and electrically efficient as possible. The overall structure of the design is broken up into three main parts: the DC-DC converter, the DC-AC converter, and the control system. The DC-DC converter takes the solar panel output which is around 48VDC and steps up the voltage to around 400VDC which is needed for the next stage. Then the DC-AC converter takes the 400VDC voltage and converts that to a three-phase sine voltage for the grid. These actions are possible due to fast transistor switching, a transformer, rectifying diodes, and filtering. The last component is the control systems which is done by a microcontroller. This senses voltages and currents along the process and makes sure it is stable and interacts with the grid properly. We currently have a working prototype which includes multiple PCBs.

Emilie Karovic

Major: Molecular & Cell Biology, Psychological Sciences

Student Bio: Emilie is a Molecular & Cell Biology and Psychological Sciences double major and a STEM Scholar within the Honors Program. She is also a team captain of the UConn DI Women’s Rowing team. Emilie is currently completing her Honors Thesis in the Core Lab within the Institute for Systems Genomics. She studies a single nucleotide polymorphism (SNP) in chromosome 16 that has been shown to be associated with Chronic Lymphocytic Leukemia (CLL). The SNP is hypothesized to cause isoform switching from a complete functional transcript of IRF8 to a short dysfunctional isoform, potentially contributing to the genetic component of CLL etiology. Emilie also serves as a research assistant in the UConn SHARP lab in the Psychology Department, where she assists in the design, data collection, statistical analysis, and upcoming publication of multiple research studies focusing on well-being, health, and social attitudes.

Title of Thesis: Verification of IRF8 Transcript Isoform Switching Due to CLL-Associated Enhancer SNP

Chronic Lymphocytic Leukemia (CLL) is the most common form of leukemia in adults (~25% of leukemia cases) and is characterized by a build-up of B-lymphocytes. The cause of CLL is unknown, but significant evidence suggests that there is a genetic component. There is an 8% increased prevalence of CLL in first-degree relatives, nearly double the risk factor for other cancers. Genome-wide association studies (GWAS) identified 41 loci in the genome that are associated with CLL. My research focuses on a single nucleotide polymorphism (SNP), rs305088, that occurs in chromosome 16 and has been shown to be associated with CLL. The SNP is located within an enhancer downstream of the IRF8 gene. The IRF8 transcription factor is thought to be relevant to CLL etiology because it controls key events in B-lymphocyte development and function. My research aims to validate previous findings from published data and RNA-seq analysis that this SNP is causing isoform switching from the complete functional transcript of IRF8 to a short dysfunctional isoform and potentially contributing to the genetic component of CLL etiology. To validate the findings, I need to find a cell line with a normal allele (no SNP) to compare to the CLL cell line that has the risk allele (has SNP). I used Sanger sequencing to genotype B-lymphoblast cell lines to determine if each candidate cell line had the normal or risk allele at the SNP location. RT-qPCR was used to determine if the IRF8 gene was active and also to detect increased expression of the short IRF8 isoform in the CLL cell line compared to a normal B-lymphoblast cell line. Northern blot analysis will be performed to compare the normal genotype cell line to the CLL cell line to measure whether expression of the IRF8 short isoform and the full IRF8 isoform change depending on SNP genotype.

Nicole Khusid

Major: Physics, Computer Science

Minor: Astrophysics

Student Bio: While I am from the Philadelphia area, I came to UConn because of the camaraderie I felt upon visiting campus. I changed and added to my major a couple of times at the beginning of my undergraduate career, but I quickly settled into my passion for physics before diving even deeper into astrophysics research for the remainder of my time at UConn. I've become involved with many campus activities, including teaching and coaching group fitness classes at the rec center. I generally love to be active outdoors, but when it’s too cold to do so I enjoy reading and playing piano. After graduating, I will be pursuing my PhD at Stony Brook University starting this fall. I am grateful for all the ways in which UConn has equipped me to take on this next step in my career, and I am excited to continue on the path towards becoming a “Space Doctor.”

Title of Thesis: Multimessenger Gravitational Wave Signals from Strongly Lensed Supermassive Black Hole Binaries 

Gravitational wave signals from supermassive black hole binaries, the most powerful emitters, can currently only be detected using pulsar timing arrays. So far, a detection of GWs from such sources has not been made due to limited PTA sensitivity to the amplitude, or strain, of the signals. I propose the use of strong gravitational lensing as a tool to improve PTA detection efforts in the era of the Square Kilometer Array telescope via the magnification of the GWs from lensed SMBHB sources. With the presence of strong lensing, we are able to probe a greater detection volume and broader SMBHB parameter space for a greater number of sources producing detectable GWs. I develop a computational framework that inputs a mass function, evolving binary fraction, and strong lensing probability to calculate the cumulative distribution of detectable, strongly lensed SMBHBs within a given redshift volume. This lensed population is particularly intriguing because the strong lensing regime yields multiple images of a source, within which we should be able to resolve the black holes' electromagnetic counterparts, allowing us to image these binaries for the first time. Additionally, great enough time delays between images would allow us to track the binary's GW frequency evolution over time by detecting the signals from different images in different PTA frequency bins. I investigate the overlap in detectable SMBHB parameter spaces for resolvable EM signals as well as for resolvable GW frequency evolution in an effort to predict the existence of at least one such “golden” strongly lensed SMBHB that would provide us with rich multimessenger information.

Ashley Kovach

Major: Physiology & Neurobiology

Minor: Molecular & Cell Biology

Student Bio: Ashley Kovach is a second-semester senior majoring in Physiology & Neurobiology and minoring in Molecular & Cell Biology. Ashley’s involvement in undergraduate research began during the Spring 2021 semester with the Salamone Lab in which she is now completing her honors thesis titled: “The Atypical Antipsychotic Cariprazine Induced Motivational Impairments in an Animal Model of Avolition: Implications for the Treatment of Schizophrenia”. Outside of academics, Ashley finds community as a member of Kappa Alpha Theta and UConn Red Cross Club, as well as being President of Greek Intervarsity. After graduation, Ashley will be attending Roseman University of Health Sciences in Utah to obtain a second bachelors in nursing through their accelerated program.

Title of Thesis: The Atypical Antipsychotic Cariprazine Induced Motivational Impairments in an Animal Model of Avolition: Implications for the Treatment of Schizophrenia

Cariprazine is an atypical antipsychotic used to treat schizophrenia. Traditional antipsychotics are D2 receptor antagonists, and have proven to be effective in treating positive symptoms such as hallucinations and delusions, but are relatively ineffective at treating negative symptoms. Cariprazine is a third-generation antipsychotic that works as a D3/D2 receptor partial agonist. Clinical data suggest it can decrease both positive and negative symptoms as measured by standardized questionnaires. Potentially due to its partial agonist activities, various animal studies reported that cariprazine may treat certain negative symptoms such as cognitive deficits, social behavior and sucrose-preference. Other negative symptoms in schizophrenia include avolition, anhedonia, blunted affect, and alogia. In Salamone Lab, we use effort-related choice tasks to model avolition in rats, which is characterized by a lack of motivation and goal-directed activity. The rats are trained on Fixed-Ratio (FR) 5/chow feeding choice task, in which rats can either press a lever for a pellet of highly-palatable food or eat less-desirable chow readily available in the chamber. If cariprazine is useful for treating all negative symptoms of schizophrenia, including avolition, then it should increase exertion of effort in our model. However, our results showed that cariprazine actually decreased exertion of effort, as there was a decrease in lever pressing and a compensatory increase in chow intake after cariprazine administration. Given this, it is possible that cariprazine is acting more like a D2 antagonist, which typically produces a shift from lever pressing to chow intake in effort-based choice models. Another explanation could be that reductions in D3 receptor signaling dissociate the different negative symptoms, so that avolition is made worse but the other negative symptoms are improved. Future studies may focus on the effects of various antipsychotics on different negative symptoms that potentially have distinct neuronal mechanisms, in order to improve therapeutics for schizophrenia and other mental disorders.

Rachit Kumbalaparambil

Major: Mechanical Engineering

Student Bio: Rachit Kumbalaparambil is a senior Mechanical Engineering major and a creative at heart. An early love of cars and planes propelled him into the field of engineering, and while it can be challenging, he enjoys the innovative aspect of it—whether it be designing a system from scratch or simply having the creative freedom of choosing what size nuts and bolts to use. Outside of classes, Rachit is the president of Breakdancing Club at UConn, and he enjoys a variety of other activities including video editing, graphic design, skateboarding, playing guitar, speedrunning Wordle, and hanging out with friends, family, and his cat Dixie.

Title of Thesis: Inverted Pendulum Sensors and Mechanical Components Analysis 

The inverted pendulum is a classic control systems project and a novel example of an engineering application. One of the most prominent examples of an application of an inverted pendulum control system is in booster rockets at takeoff, which ensure the rocket maintains its upright position. Now, my project is not a booster rocket, however it is a small scale model of the working control system in an inverted pendulum. The 2 main components in the system consist of a rotary encoder and a stepper motor with encoder. The encoder functionality is necessary to provide the control systems with information that has a high enough degree of accuracy regarding the dynamics of the system. In this small scale rig there are many other mechanical parts as well as sensors working together, and my project involves an in depth overview of the functionality of these parts in the context of the system. This will include analysis of the specifications of these components and translating them into respective applications based on recommended ranges for practical use. It is often unclear what specifications are needed for a given application, and this project aims to provide a comprehensive guide which will help better understand the applications of sensors and other mechanical parts in different usage scenarios, while using the parts in the inverted pendulum assembly as a reference.

Callista Lajeune

Major: Molecular and Cell Biology

Minor: Women's Gender and Sexualities Studies

Student Bio: Hi, my name is Callista Lajeune. I am a Molecular and Cell Biology Major with a Women's Gender and Sexualities Studies Minor, on the pre-med track. Throughout the past four years as a STEM Scholar and honors student, I have met some great people and been presented with great opportunities. I have been part of a couple of research labs and also became a Research Assistant at Connecticut Children's. Besides medicine and academics, I am interested in dance, music, anything Disney, and prioritizing mental health. I can't believe graduation is so soon, and I am excited to see where my fellow scholars and I will end up in this world!

Title of Thesis: Comparing SARS-CoV-2 Antibody Tests from Quest Diagnostics and Jackson Laboratories Utilized to Identify MIS-C Patients 

COVID-19 is a respiratory illness caused by the virus SARS-CoV-2. People infected with the illness usually are either asymptomatic or ill with mild respiratory and flu-like symptoms. i On the other hand, severe symptoms could require hospitalization. Notably, numerous children infected with COVID-19 have been diagnosed with Multisystem Inflammatory Syndrome in Children (MIS-C) about a month after SARS-CoV-2 infection. MIS-C is characterized by an inflammatory reaction that targets multiple organ systems in children. Diagnosing MIS-C is difficult because the clinical phenotype overlaps with pediatric viral infections and Kawasaki disease, a non-COVID related inflammatory disorder. Although there is no specific test available for diagnosing MIS-C, because MIS-C patients have evidence of prior SARS-CoV-2 infection, an antibody response is expected.

Currently at Connecticut Children’s Medical Center, there is an ongoing prospective cohort study investigating the biomarker signature of MIS-C. In addition to the clinical Quest Diagnostics antibody testing, study samples are being assessed by a validated, highly specific and sensitive antibody and neutralization assay developed by Jackson Laboratories. Anecdotally, the results of the two methods of antibody testing have not always yielded the same results. For example, The Jackson Laboratories antibody test had a positive result for a patient, while the Quest Diagnostics test reported a negative result.

As MIS-C diagnosis is often conditional on a positive antibody test, defining the test characteristics of commercially available tests to the Jackson Laboratories gold standard is critical. Therefore, we plan to determine the sensitivity, specificity, and positive/negative predictive values of the Quest Diagnostics antibody tests to the Jackson Laboratories antibody tests in a cohort of patients enrolled in “Identifying Biomarker Signatures of Prognostic Value for MIS-C" prospective study.

Rebecca Lee

Major: Chemical Engineering

Minor: French

Student Bio:Hi I'm Rebecca and I will be graduating with a major in chemical engineering and a minor in French. My research focuses on implementing a 3D-printing technology to improve the productivity of bioethanol purification, and I've also been involved in a startup company, Aqualumos, that is developing photocatalytic reactors to treat Per- and Polyfluoroalkyl Substance (PFAS)-contaminated waters. My interests lean towards engineering solutions towards environmental sustainability, and I aim to continue my work in this area by pursuing a PhD in chemical engineering at the University of Texas in Austin starting this fall.

Title of Thesis:Development of 3D-printed membranes for the production of low-carbon intensity biofuels

Rising energy demands and the excessive consumption of fossil fuels have led to increased greenhouse gas emissions, scarcity of resources, and fluctuating fuel prices. This has led some to consider renewable bioethanol as a promising source of alternative energy, especially due to the wide availability of biomass and recent efficiency gains in corn-to-ethanol conversion. However, the efficiency of bioethanol processing still remains limited due to the energy-intensive distillation and molecular sieving processes currently used to purify the dilute ethanol solution from fermentation. Pervaporation, a method of membrane separation, has the potential to address the limitations of both distillation and molecular sieving given it can demonstrate the stability, selectivity, and low capital cost required for commercial viability. Capital cost, in particular, poses a challenge to conventionally-casted pervaporation membranes as their uncontrolled and relatively high thicknesses limit their throughput and require larger membrane areas. In this study, a novel additive manufacturing process known as electrospray was implemented to fabricate one of the first thin-film composite pervaporation membranes for ethanol dewatering in order to improve flux without a decline in selectivity. Using this method, layers of polyvinyl alcohol (PVA) and glutaraldehyde crosslinker were deposited in the presence of a strong electric field to create ultrathin films over a polyacrylonitrile substrate. The calculated thicknesses of 3D-printed, crosslinked 5% PVA membranes produced through additive manufacturing were notably thinner than the 30-plus microns typically observed for casted PVA membranes. Membrane performance testing using a benchtop pervaporation system was used to determine the flux and selectivity of printed membranes relative to commercially-available and previously-studied membranes.

Jacob Lenes

Major: Computer Science and Engineering

Minor: Mathematics

Student Bio: Hello! I am a senior studying Computer Science & Engineering with a concentration in Cybersecurity and a minor in Mathematics. I have a deep interest in Computer Security, and love to work with Linux. This past summer, I had the opportunity to do Cyber Security Engineering for IEX, a stock-exchange based out of NYC. It was a great opportunity to get hands-on experience in the realm of Cyber Security. When I am not doing schoolwork, I like to go for walks with my 5 dogs (3 greyhounds, 2 jack russell mixes), hang out with friends, and go on adventures. My most recent adventure was skydiving, which I plan to do again once I move after graduation.

Title of Thesis: The assistance of Applied Introduction to Cryptography, as well as Cyber Security Academia 

Over the course of my senior year, I have been assisting professor Amir Herzberg for my Honors Thesis Project. I was tasked with helping him in creating exercises for his Cyber Security courses, such as CSE 3140, The Cybersecurity Lab. Along with this, I had the intention of getting some of these exercises added into his textbook, Applied Introduction to Cryptography. These exercises ranged from differing Cyber security topics, such as common modern-day attacks and asymmetric key encryption algorithms. One exercise included creating ransomware programs, requiring students to figure out how to decrypt certain files. Another generates separate plaintext and ciphertext per student in the class, encrypted with the El Gamal encryption scheme, requiring students to decrypt with understanding of the discrete log problem. Many of the tasks that Professor Herzberg gave required me to spend several days researching and better understanding the topics on which I would create exercises on. It became apparent that one can always learn more about a topic. Thus, this project involved helping Professor Herzberg with academia, as well as assisting him in his courses. It was extremely rewarding, and I would like to thank Professor Herzberg for all of the time and efforts he put into helping me with this year-long project. My final paper will mainly be focused on the exercise and code that I created, including what I have gained/learned through helping him, and next steps.

Malavika Madan

Major: Physiology and Neurobiology

Student Bio: My name is Malavika and I am a Physiology and Neurobiology major on a premed track. I was born in India and my family relocated to the States in 2013. I have, since, been fascinated as well as amused by the vast cultural differences between the two countries. Shortly after my relocation, I started school at the Academy of Aerospace and Engineering alongside taking part in various programs across the state of Connecticut. I, soon discovered my interests to be within the fields of science. When I started off as a freshman at UCONN, little did I know, that I would be drawn to the study of human physiology and neuroscience. As a graduating senior today, I have only developed a deep sense of fascination and appreciation for the human body and hope to continue these pursuits as a healthcare professional in the future.

Title of Thesis: Drug Delivery Systems of Glioblastoma Multiforme

Glioblastoma Multiforme (GBM) is one of the most prevalent and malignant brain tumors known to the world today and is referred to as a Grade IV astrocytoma. GBM has an incidence rate of 3.19 per 100,000 persons in the United States however, its rate of recurrence is much higher. Current, standard treatment for GBMs is a surgical resection followed by radiation and chemotherapy, however, complete tumor removal still remains a challenge. GBM’s genetic heterogeneity, poor infiltration nature, high immunosuppressive activity, tumor microenvironment including the presence of GBM stem cells as well as the Blood Brain Barrier (BBB) pose numerous challenges that make it impossible to ever remove the tumor completely. Thus, there is an urgent need and an increased interest in research involving the development of novel strategies to overcome these challenges, particularly, with nanotechnology drug delivery systems. Nanotechnology and nanocarrier based drug delivery systems have recently gained massive support because of their characteristics like nontoxicity, increased solubility, biosafety, sustained drug release, BBB permeability as well as enhanced drug bioactivity. Present studies focused on the optimization of GBM treatment favors controlled delivery of therapeutic drug compounds such as antitumor antibiotics like doxorubicin, epirubicin, bleomycin, actinomycin D etc, through the BBB to the tumor microenvironment via nanocarriers and monoclonal antibodies. Specifically, recent developments have revealed that the conjugation of nanoparticles with nanocarriers such as liposomes, polymeric micelles, metal irons and dendrimers have efficiently been able to penetrate the BBB enhancing drug-compound delivery at the tumor site. Therefore, the aim of this review is to provide a culmination of past research investigating novel drug systems as a potential treatment for Glioblastoma Multiforme. Furthermore, this review will also address advantages, challenges and various types of novel drug systems that have been investigated. Currently, surgery is used to remove solid tumor tissue that may be resistant to radiation and chemotherapy. Thus, prolonging the lives of patients and improving the quality of remaining life. However, in the future, drug delivery approaches will enable direct access to the tumor overcoming current challenges, leading to immediate adaptations of tumor-tailored targeted therapies.

Jamie Masthay

Major: Psychological Sciences

Minor: Neuroscience

Student Bio: I am a psychology major and neuroscience minor from Simsbury, CT. My undergraduate research has focused mainly on psychopharmacology and its applications in treating psychiatric disorders. Since my sophomore year, I’ve been working in Dr. John Salamone’s lab in the Psychology department. In particular, I have done a lot of work studying the neurotransmitter dopamine and its role in motivation, as well as how dopamine dysfunctions contribute to disorders like depression and schizophrenia. My Honors thesis project has focused on preclinical studies of novel drug treatment options for binge eating disorder to hopefully improve clinical outcomes for patients. After graduating from UConn, I will be pursuing my PhD in psychology with a concentration in neuroscience at Yale University, starting this fall. In my free time, I enjoy hiking, gardening, reading science fiction novels, and spending time with my cat.

Title of Thesis: Characterization of the Catecholamine Uptake Inhibitor Bupropion and the Opioid Antagonist Naltrexone, Alone and in Combination, on Binge-Like Eating Behavior

Binge-eating disorder (BED) is characterized by periods in which an individual consumes a large amount of highly palatable food in a short time, accompanied by feelings of distress or lack of control over food intake. BED is modeled in animals by inducing binge-like eating of palatable foods. The only FDA-approved drug treatment for BED is the stimulant lisdexamfetamine, but variability in patient responsiveness indicates a need for more robust treatment options. Bupropion (BUP) and naltrexone (NTX) have been suggested as novel BED treatments based on their weight-loss effects and ability to reduce palatable food intake in animal models. Additionally, the combination of the two (NB) is a standard in the treatment of obesity, and has been theorized to be an effective treatment for binging. In this project, we examined the effects of BUP and NTX, alone and in combination, on binge-like eating behaviors in male and female rats. Binge-trained rats were divided into three groups (BUP alone, NTX alone, NB) to determine what drug each animal would receive, after which behavioral testing examined the drugs’ effects on their food intake. All three treatments significantly reduced palatable food intake. Sex differences were seen at several levels; these differences are notable because BED is more common in female populations, and they indicate that future studies of BED treatments should take sex differences into account. The results of this study suggest that BUP, NTX, and NB could all be efficacious in the treatment of BED. This work contributes to the development of novel treatment options for BED, in the hopes of improving clinical outcomes.

Roshni Mehta

Major: Molecular and Cell Biology and French

Student Bio: Roshni is a dual degree MCB (molecular cell biology) and French major from Scarsdale, NY. Her unusual combination of majors allows her to explore her love for STEM subjects as well as language and literature. The STEM Scholar program has been an integral part of her university experience as it allowed her to meet and bond with other students pursuing similar studies. After graduation from UConn, she plans on attending Université de Toulouse III-Paul Sabatier located in Toulouse, France for a Masters Degree, and later hopes to apply to medical school. In her spare time, Roshni loves to be with friends or family, and read, particularly historical fiction.

Title of Thesis: Who Let the DoGs Out? An Analysis of RNA Transcription Readthrough and Termination 

The central dogma of biology is a process in which DNA is transcribed into RNA which is then translated into an amino acid sequence to produce a protein. The production of an RNA copy, also known as gene transcription, is a highly regulated process; however, some abnormalities and alternative means of production have been observed. DoGs, or downstream of gene containing transcripts (coined by Vilborg et al., 2017) occurs when transcription occurs further down the normal gene end. My research focuses on how the process of transcriptional termination is altered, producing such transcripts.


Mohsin Mirza

Major: Molecular and Cell Biology

Student Bio: I am a Molecular and Cell Biology student interested in the biomedical field. After conducting clinical research at UConn Health in orthopedic surgery and Connecticut Children’s in the emergency department, I transitioned to wet lab research after being hired by DeBogy Molecular in the spring of 2021.

Since then, I have worked extensively to expand our capacity for research and development at this stealth startup. I have done research in chemical synthesis, surface chemistry, and microbiology in this role in an effort to bring self-sterile surfaces to market.

I hope to apply the experience and knowledge I have gained over the last 4 years as I continue with DeBogy Molecular while attending the University of Connecticut School of Medicine next year.

Title of Thesis: Evaluating Antimicrobial Surface Modifications on Various Industry Materials

Surface microbes have a detrimental impact for many different reasons. In the biomedical field, contamination of bacteria and viruses leads to infections that cause poor health outcomes for patients. Treating these secondary issues ultimately results in immense cost on the overall healthcare system. Medical device associated infections make up 50-70% of the yearly 2 million healthcare associated infections in the United States, oftentimes caused by biofilm formation on things like orthopedic implants or urinary catheters.

Microbial surface contamination is also associated with huge environmental waste. Single use disposable medical instruments and personal protective equipment contribute more and more to pollution, especially since the onset of the coronavirus pandemic. Moreover, current treatment options for surface microbes only work to amplify this issue. Single use wipes and disinfecting sprays are wasteful while also resulting in chemical runoff back into the environment. The end result of this is a positive feedback loop that worsens both climate change and antimicrobial resistance.

Nearly every industry in our world stands to benefit from safe and effective antimicrobial surface modifications. In my thesis, I modified surfaces modified with quaternary ammonium compounds, which are known to have an antimicrobial effect. I treated a variety of materials used in industry, then conducted microbiological testing to verify that these materials effectively prevented bacterial growth, and subsequently, biofilm formation.

After seeing how effective this treatment is, I hope to see antimicrobial surface modifications incorporated into different industries and fields because the applications are truly endless.

Ranita Muriel

Major: Molecular and Cell Biology

Minor: History

Student Bio: My name is Ranita Muriel, and I am from Shelton, Connecticut. I am a student in the Honors Program majoring in Molecular and Cell Biology and minoring in History. My academic interests are focused in clinical research related to health outcomes. During my time at UCONN, I was able to participate in the Undergraduate Research Assistant Program at Connecticut Children's Medical Center, which deepened my love for pediatrics. Additionally, I was able to pursue my love for understanding history through an independent study I did on St. Augustine's Transvaluation of the Classical Tradition. In my spare time, I have enjoyed volunteering as an EMT and being involved in the Catholic Center on campus. I am grateful the friends and memories I have made at UCONN!

Title of Thesis: Injuries Sustained by Pediatric Motor Vehicle Accident Victims 

For my honors thesis, I investigated the types of injuries sustained by pediatric motor vehicle accident victims by conducting a retrospective cohort study using the CT Injury Surveillance System Database. The last revision to car seat legislation was made on October 1, 2017. Since then, no studies have examined the types of injuries sustained by pediatric victims of motor vehicle accidents. Changes in car seat laws may have elicited changes in injuries sustained. With this in mind, I evaluated relationships between time intervals, injury types, age categories, gender, and race. My study found that there was a drastic decrease overall in ED admittance, but an increase in motor vehicle accident related admittance after October 1, 2017. Additionally, there was an increase in head and neck, chest and back, and abdomen and pelvis injuries, and ages 8-13 years old were the most likely to sustain injury in all injury categories in both time intervals. Furthermore, there was an increased incidence of injury in females for chest and back, abdomen and pelvis, and extremity injuries. African Americans and Asians followed by Native Hawaiian/Pacific Islanders had an increased incidence of injury. The conclusions that can be drawn from my findings are that car seat legislation has not positively impacted injury occurrence between 2014 and 2020. The cause of this is unknown and further research on the cause of this increase in motor vehicle accident related injuries must be conducted. Future research should look at child restraint usage among the age, race, and gender categories used in this study. I hope that this study provides a foundation for an increased capacity in post-accident care in Emergency Departments, and positive change in regards to child restraint education and usage.


Marissa Alba Naclerio

Major: Natural Resources & the Environment

Student Bio: Marissa (she/her) is studying Natural Resources and the Environment with a concentration in Conservation and Sustainability. Her academic interests lie in intersectional environmentalism and environmental justice, as well as disturbance and urban ecology. She has participated in study abroad programs to South Africa and Turks & Caicos, where she became a certified scuba diver. Marissa has completed a Research Experience for Undergraduates (REU) at the Pennsylvania State University for Climate Science and currently conducts research in the Morzillo Human Dimensions Lab here at UConn. Beyond the classroom, she is passionate about advocating for environmental justice and cultural awareness. She is deeply involved with the Puerto Rican-Latin American Cultural Center, where she promotes cultural competency and celebration through dance, education, and mentorship. Marissa is also involved with the Louise Stokes Alliance for Minority Participation, for which she has also mentored.

Title of Thesis: Tracking Changes in Greenness in a Mangrove Forest Following Hurricane Irma in the Florida Everglades

Mangrove forests are one of the most effective ecosystems for carbon sequestration, yet they are experiencing more frequent hurricanes due to the changing climate. Hurricane Irma, which made landfall in southwestern Florida during September of 2017, brought severe conditions which triggered defoliation and tree mortality among mangrove forests located in the Florida Coastal Everglades Long Term Ecological Research Network (FCE LTER). Using data from 2019 collected by an eddy covariance tower within the Everglades National Park (25.3646°N, 81.0779°W), this study measured post-hurricane net ecosystem exchange (NEE) rates and NDVI values for a tall riverine mangrove forest located along Shark River Slough. Post-hurricane NEE values were compared to pre-hurricane values reported for the study site. Additionally, I visually compared images of the flux footprint model for 2017 (pre-hurricane) and 2018 (post-hurricane) showing tree mortality and defoliation and determined patterns in NDVI over the course of 2019. Results indicate that the average post-hurricane maximum photosynthetic rate was -9.99 µmol (CO2) m-2 s-1, as compared to −20 to −25 μmol (CO2) m−2 s−1 measured prior to the storm (2004-2005). Determinedly, carbon dioxide (CO2) uptake in the mangrove forest decreased as a result of Hurricane Irma. Further results indicate that NDVI was consistently higher during the summer wet season, indicating higher levels of ecosystem productivity than during the winter dry season. Looking forward, examining the response of mangrove forests to hurricanes, such as Hurricane Irma, allows us to better understand the resilience of mangrove forests and their capacity for climate change adaptation and mitigation.

Anusha Nagella

Major: Computer Science and Engineering

Minor: Mathematics and Communications

Student Bio: I am currently a senior studying Computer Science and Engineering in the School of Engineering. I am concentrating in Computational Data Analytics and have taken courses in Machine Learning, Artificial Intelligence, etc. These courses have set me up well for the foundation of my thesis research. I also love to share my love for computer science with others through my roles as a Teaching Assistant and founder of Women in Computer Science. Outside of my academics, I love to work out, bake when I get the chance, and spend time outdoors! After college, I am looking forward to working as a Software Engineer and applying what I have learned in the classroom in the real world.

Title of Thesis: Detecting Depression Dialogue on Twitter 

While the Covid-19 pandemic has caused detrimental effects on the physical health of many, it has also been causing a widespread decline in mental health. With isolation during quarantines, negative media coverage, economic downfall, and general death/loss due to the disease. Especially with a lack of social interaction due to the multiple quarantines throughout the pandemic, the usage of social media has increased greatly. We see an increase in individuals using social media to share their feelings. The objective of this research project is to define a classification framework that most accurately classifies depression dialogue, specifically on the platform Twitter.

The first level of classification is classifying between “Relevant” versus “Non-Relevant” tweets. When considering a tweet that is classified as “Relevant”, this signifies the tweet is about depression in terms of mental health. “Non-relevant” tweets are those that may speak of depression irrelevant to mental health, for example, about the Great Depression. The second level of classification is classifying between “Personal” vs. “Informational” Tweets. This classification looks specifically at tweets regarding depression relevant to mental health. “Personal” tweets are classified as such if they are sharing personal experiences, anecdotes, and opinions about depression. “Informational” or PSA tweets are classified as those that share promotional services for help or other informational purposes.
Using machine learning and neural networks, I have developed, tested, and compared the metrics of a variety of classification model frameworks to find which framework has the best performance.

Cat Odendahl

Major: Chemical Engineering

Minor: Mathematics

Student Bio: Cat is a senior chemical engineering major who plans on pursuing her PhD in chemical oceanography post graduation. She is an Aries and shows it through her various leadership roles on campus including a supplemental instruction leader for organic chemistry, section leader in marching band, middle school science bowl co-coordinator, and the creator of a local twerk team. Her style consists of bright neon colors and fly shoes which compliment her "always on the grind" attitude. She has been involved in research since freshman year and has developed her honors thesis with the help of Dr. Kristina Wagstrom. Her end goal is to be a professor in the oceanography field and to pioneer cutting-edge research in chemical oceanography. You can find her in E2 most of the time if she is not at Up and Atom visiting her best friend. Cat has drive, power, she stays hungry, and she devours.

Title of Thesis: Designing an Improved Artificial Reef-Ball to Mediate Shoreline Erosion

As climate change progresses and the sea level rises, coastal ecosystems and sediment budgets are being disrupted. To counteract the erosion that is occurring, various solutions have been presented, from increased vegetation to concrete structures that will reflect waves. One such solution is using reef balls, porous concrete artificial reefs that are designed for replacing live reefs, as submerged breakwaters. Current research is proving that these reef balls decrease the wave energy that reaches the shoreline, however their original purpose was not designed for this. Knowing this, an optimal artificial reef structure with intent on wave attenuation can be considered. Through this research, the optimal artificial reef is laid out by observing experiments and simulations that change the number of holes on the reef, the size of the holes, ratio of the top to bottom reef area, top and bottom shape, thickness, and hole shape to find the best combination to lessen the energy that reaches the depleting shoreline.

Mehreen Pasha

Major: Molecular and Cell Biology

Minor: Spanish

Student Bio: Mehreen is grateful for the knowledge, skills, and mentorship she gained as a University Scholar, IDEA Grant recipient, and STEM Scholar at UConn. She has a passion for sharing her love of science through BIO 1107 Mentoring, Integrated Refugee & Immigrant Services (IRIS) high school tutoring, and Sci-Art Gallery. Outside of the sciences, she is a proud Pakistani-Muslim woman having a fascination with languages—taking Spanish and Korean language courses to complement her STEM coursework. When she isn’t at the lab bench, she enjoys running, watching kdramas, and getting boba with friends. She is excited to attend UConn School of Medicine this fall and continue research in clinical settings.

Title of Thesis: When Problems Become Solutions: Harnessing the Osteogenic Capacity of Disease-Causing Stem Cells to Repair Bone Fractures

While we often perceive disease as negative, there is potential to engineer seemingly negative biological phenomena into therapeutics to treat human disease. The Goldhamer Lab at UConn studies a genetic disorder known as fibrodysplasia ossificans progressiva (FOP), which involves uncontrolled, widespread bone growth outside of the skeleton. In FOP patients, cells called fibro/adipogenic progenitors (FAPs) follow an abnormal pathway and turn into bone. My project investigates whether mutant FAPs, which are exceptional at producing bone, can be used to repair bone fractures in otherwise normal patients. I have two primary aims: (1) to develop and optimize a novel, minimally invasive approach for modeling bone fractures in mice without physically fracturing bones, and (2) to examine osteogenesis (bone formation) after introducing mutant FAPs at the site of bone fracture and see whether they repair bone faster than traditionally used stem cells. As it was found that mutant FAPs form bone when in the presence of either bone morphogenetic proteins (BMPs), which are found near bone, and/or activin A, which is found all over the body, I will introduce an agent that blocks activin A and test whether FAP-meditated bone deposition can be highly localized to bone fracture sites.

Amisha Paul

Major: Physiology and Neurobiology & Economics

Minor: Global Studies and Anthropology of Global Health

Student Bio: Amisha, from Southington, CT, is pursuing a B.S. in Physiology and Neurobiology and B.A. in Economics, with minors in Global Studies and Anthropology of Global Health. On-campus, she served as the Executive Director of UConn Global Health Spaces on Campus, organizing UConn's annual Global Health Symposium and Hackathon in efforts to encourage awareness and dialogue surrounding current challenges and progress in global health. She has also been recognized as a UN Foundation Global Health Fellow and a Millennium Fellow. She is engaged in developmental neurobiology research on campus in Conover Lab as well as in health economics research. Amisha also serves as a Trip Director with UConn Community Outreach's Alternative Breaks Program. Amisha enjoys performing as a trained Odissi dancer and promoting Indian classical arts on campus in her role as Co-President of Sanskriti, UConn's Indian Classical Arts collaborative. She also enjoys traveling, learning new skills, and collecting stories.

Title of Thesis: Understanding Ventricular-Subventricular Zone Development: Neural Stem Cell Lineage Tracing and Structural Configuration Modeling

This project seeks to understand the development and function of the ventricular-subventricular zone (V-SVZ) stem cell niche, an area essential for human brain development and for overall brain function. In early brain development, the neural tube lining as well as the ventricular system host proliferative cells that contribute to the development of the cerebral cortex. Neuroepithelial cells give rise to radial glia, which in turn differentiate into neural stem cells and ependymal cells. These ependymal cells provide a crucial barrier and transport functions of cerebrospinal fluid in the ventricular system. As development continues, the stem cells give rise to more ependymal cells that are conformed in pinwheel structures, and the stem recede to the subventricular zone surface. In order to characterize this development, I have collected and processed mouse tissue samples that will act as snapshots of developmental progression as stem cells generate new immature ependymal cells which then go on to mature into functional, multi-ciliated ependymal cells that line the ventricular system of the brain. This data will be used to create computational models of stem cell-mediated differentiation and organization along the ventricular system. I have also used 3-d softwares to model ventricular size and structural changes in early human brain development.

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Sucika Perumalla

Major: Physiology and Neurobiology

Minor: Bioinformatics

Student Bio: My name is Sucika Perumalla, and I am PNB major and Bioinformatic minor. In my sophomore year, I joined the STEM Scholar EBoard as the Co-Social Engagement chair, where I have assisted the team in organizing in reaching our goal of bringing students together from various STEM backgrounds. Additionally, I encouraged students to explore a diverse range of STEM through networking, informative panels, research, and internship opportunities. I especially enjoyed arranging the Diversity Panel and STEAM bowl events this past year. Additionally, I am the Vice President of TEDxUConn. I am actively involved in curating student enthusiasts and professors in our local community who are passionate about sharing their knowledge on a professional platform at our conferences. I have also been a volunteer for Paper Airplanes for over two years, where I support individuals who were negatively impacted by the Syrian-Palestine crisis. In my free time, I embrace my Indian culture and its classical art forms as the Co-President of UConn Sanskriti.

Title of Thesis: Behavioral Response to Changing Emotional Environment: Effects of Dorsal Hippocampus Inactivation

Fear is defined as a behavioral response that enables organisms to protect themselves from environmental threats (Mobbs et al, 2019). The amygdala is an important brain structure for the processing of emotions, like fear and anxiety. When rats are placed in anxiety-stimulating situations there is increased neuronal firing in the amygdala related to fear memories (Markram et al. 2007). In addition to the amygdala, the ventral hippocampus also correlates with emotion-related memory retrieval and receives input from the amygdala to consolidate new memories. When this region was lesioned in male rats, they demonstrated less anxiety-related behavior (Wang et al., 2019). In contrast to the ventral region, the dorsal hippocampus has been associated with spatial navigation (McEown and Treit, 2010). However, the inactivation of the dorsal hippocampus in rats resulted in impaired fear memory retrieval. Consequently, it seems that the dorsal and ventral hippocampus interact when processing information that has both an emotional and spatial component (if you think of it, this is true in most “real life” situations).

Under natural conditions the animal has a choice of conflicting options, foraging for food or avoiding danger, both of which are essential for survival. This experiment will attempt to mimic this situation in a laboratory setting when rats must forage for food under a “safe” and “unsafe” condition. In the unsafe condition, the rats hesitate before crossing a maze region with a mild current. The degree of hesitation is a measure we use to monitor their fear level. The goal of the current study is to record single ventral hippocampal cells, while using chemogenetics to transiently inhibit dorsal hippocampal activity. This will provide insight into how the ventral hippocampus processes changing contextual information and the contribution of the dorsal hippocampus to this activity.

Julia Quinn

Major: Biological Sciences

Minor: Urban and Community Studies

Student Bio: Julia is a senior majoring in Biological Sciences and minoring in Urban and Community Studies. She has been a member of the Core Lab since the fall of 2019, where they are interested in understanding how changes in RNA transcription and processing drive changes in cellular states and the development or progression of disease.

Aside from research, Julia is interested in improving health outcomes in her community. She is apart of the UConn Health Leaders program, where she has worked on a variety of projects including COVID-19 contact tracing, screening patients for social determinants of health, and addressing the rise in chronic opioid use disorder. Julia has also volunteered with the Health Education Center, where she served as a community health educator, delivering weekly health lessons to local underserved populations.

Next fall, Julia is excited to continue her education and pursue a medical degree at the University of Connecticut School of Medicine.

Title of Thesis: Determination of the Timing of Post-Mitotic Read-through Transcription by RNA Polymerase II

Transcription is the process by which the information stored in DNA is converted to an mRNA molecule. Since DNA remains in the nucleus, mRNA transcripts allow genetic information to enter the cytoplasm where it can be translated into proteins. This process is carried out by RNA polymerase II. However, when RNA polymerase II continues to transcribe past the 3’ end of genes, this is called read-through transcription. This phenomenon takes place during conditions of hyperosmotic stress, heat shock, oxidative stress, viral infection, and some cancers. However, the Core Lab has also found that read-through transcription takes place post-mitosis.

Since not much is yet known about post-mitotic read-through transcription, the first step in finding out why and how this happens is by determining when this phenomenon occurs. My thesis project seeks to synchronize cells through the selective inhibition of a CDK1 protein engineered to have altered specificity. This technique pauses the cell cycle at the G2/M boundary and offers a quicker and more gentle approach to cell synchronization without impacting other CDK proteins. I will then be using this method to collect cells at different cell cycle stages and look for the presence of read-through transcripts using RNA FISH. By figuring out when read-through transcription takes place, we can better understand its significance in cell functioning and potential role in human health and disease.

Khaleel Rahman

Major: Biological Sciences

Student Bio: I came to UConn interested in studying science but throughout my years here was able to explore my passion for comedy writing. I now freelance write for online comedy publications like The Onion and Reductress. Outside of school and work I love hiking and playing soccer.

Title of Thesis: Can Satire Impact Sustainability Perceptions Among Undergraduates? 

I wanted to examine whether satire could make people think more positively about day-to-day eco-friendly actions compared to traditional journalistic sources. I had UConn undergraduates articles on climate change, either from The Onion or The Washington Post. I then had them fill out a survey asking their opinions on five different aspects, or factors of sustainable actions: spending, skepticism, responsibility, support, and mobility. Satirical readers only had more positive views in the spending factor compared to journalistic readers.

Sushant Raj

Major: Electrical Engineering, Computer Engineering

Minor: Mathematics

Student Bio: Sushant, from Shrewsbury Massachusetts, is pursuing a B.S in Electrical Engineering and Computer Engineering with a minor in Mathematics. He has been actively involved with various cultural organizations, especially the Indian Students Association, for which he served as the freshman representative, media chair, chief financial officer, and president.

In his free time, Sushant likes working on DIY projects with microcontrollers and practicing Carnatic(Indian Classical) vocal music, which he has been learning since he was 9 years old. He has been working as a Robotics Software Intern for the last four years and has developed a strong interest in the field. After graduation, Sushant plans to work as a Robotics Software Engineer for Locus Robotics and pursue a Masters in Robotics from Worcester Polytechnic Institute.

Title of Thesis: Assembly Process Improvement with Co-bot

My honors thesis revolves around my senior design project that I’ve been working on for the past year. The project is sponsored by BELIMO and is called Assembly Process Improvement with Co-bot, and it revolves around automating the process of putting together a rack bearing sub-assembly used in many of BELIMO’s products. The sub-assembly requires two components to be screwed together, so the project’s scope consisted of three parts: making the co-bot capable of both gripping components and screwing them together, creating a workstation that enables the co-bot to assemble multiple sub-assemblies using part feeders and a fixture, and finally, coding the co-bot to complete the process.

The robot initially had a set of grippers attached to it, and was only capable of operating with one tool. In order to meet the objective of the project, two additional components were added to the co-bot: a 45 degree dual mounting plate and a Robotiq screwdriver. The dual mounting plate allows for two tools to be attached to the co-bot, which enabled us to connect the screwdriver and the grippers at the same time.
The workstation is designed to make the assembly process as efficient as possible. The workstation consists of two part feeders and a fixture. The part feeders enable the co-bot to create multiple sub-assemblies without human intervention, and the fixture holds the parts together while the co-bot screws them together.
Finally, the coding process was completed to fulfill the goal of creating 20 rack bearing sub-assemblies each time the program is run.

Jonathan Rucinski

Major: Management and Engineering for Manufacturing

Student Bio: My name is Jonathan Rucinski and I am a current senior at the University of Connecticut studying Management and Engineering for Manufacturing (MEM) with a specific interest in data analytics. I am also a member of the UConn Honors program, STEM Scholar Community, and MEM Society. I hold leadership positions on the STEM Scholar and MEM Society Executive Boards. Outside of the classroom, I am the treasurer and a player on the UConn Men's Competitive Ice Hockey Club team. In the future, I plan to continue my studies as a part of UConn’s MS in Business Analytics and Project Management 4+1 program.

Title of Thesis: Analysis of Flow Stress Data of Ti-6Al-4V for Application in Simulations 

The project is an analysis and comparison of the flow stress data of the Ti-6Al-4V alloy. Data from peer conducted studies will be extracted from published articles and collected for analysis. The studies in question are forms of tensile or compressive tests of Ti-6Al-4V at elevated temperatures. The data being extracted will be that of the true stress-strain graphs resulting from the studies, in addition to its differing testing conditions. Examples of these conditions may include the specific type of tensile or compressive test, heat treatment application, and the temperature of the specimen.

The goal of this study is to determine how the unique testing environments and tests impact the flow stress behavior of Ti-6Al- 4V. Using data analysis techniques it can be determined whether or not there is a relationship between these testing conditions and the flow stress behavior of Ti-6Al-4V. These relationships will be tested using linear regression techniques. A trendline will be created for each regression and used to determine the Johnson-Cook parameters for each test. The Johnson- Cook model is utilized as it was designed to interpret how a material deforms under strain rates of 103 s-1 which is consistent with the models that will be studied.
As a result, more accurate digital twins can be recreated using the Johnson-Cook parameters for use in simulations, most notably aerospace applications.

Nathan Schaumburger

Major: Biology

Minor: Mathematics

Student Bio: I am interested in mathematical modeling of biological phenomena. I work in the Yuan Monkeyflower lab where I study the genetics of pigment pattern formation. I also am working on a separate project in conjunction with UConn Health about modeling disease progression in elderly populations.

Title of Thesis: Exploring the Mechanisms of Anthocyanin Patterning Development in Mimulus Parishii 

Pigmentation patterning on plants is a classic problem that has been studied for a long time. One model of pattern formation is called reaction diffusion, where a short range self activating activator also activates a long range inhibitor. My work involves improving this model in the context of Mimulus flowers and using the model to recapitulate observed phenotypes. I also am working to discover the genetic and molecular basis for a novel phenotype observed in the progeny of a cross between two different species. After doing genetic mapping experiments, we have a candidate gene that is already known to play a role in anthocyanin biosynthesis. I incorporated this protein into the model and it will allow me to explore exactly how the gene could be causing this new phenotype.

Saumya Shah

Major: Computer Science

Minor: Molecular and Cell Biology and Chemistry

Student Bio: My name is Saumya Shah, and I am a Computer Science major with a concentration in Computational Data Analytics. I also have minors in MCB and Chemistry. Bioinformatics is a growing, interdisciplinary field focusing on the processing and analysis of biological data. It has closely aligned with my academic interests.

I started working with my PI Dr Zhou through the Health Research Program in 2019. There I analyzed the demographics, diet, and fungi species data of multiple sclerosis patients’ microbiomes, while also working on side projects related to candida in mice and white lesions. After many months of revisions and exploratory angles, this paper was published in August 2021. Working on this project taught me how to lead a project with multiple collaborators, coding practices in R, and the methods and analytical mindset for research. Besides my involvement in research, I am also the president of Jain Student Association and play flute for the UConn Chamber orchestra.

Title of Thesis: Alterations of the gut mycobiome in patients with multiple sclerosis: a bioinformatic approach

In August 2021, my PI and I published the paper “Alterations of the gut mycobiome in patients with multiple sclerosis.” I’d like to emphasize mycobiome because while you’ve probably heard of the microbiome of bacteria helping you digest food or maybe making you feel sick, you might not know that fungi live inside your gut too…for better or for worse. Although implicated in other autoimmune diseases, the mycobiome’s role in multiple sclerosis (MS) had not yet been studied until our publication.

In that paper, we found that the microbiome composition of multiple sclerosis patients is different from healthy people. The mycobiome had significantly higher diversity and inter-subject variation in pwMS than controls. Additionally, the fungal genuses Saccharomyces and Aspergillus were over-represented in MS patients. We added depth to the study by correlating the fungi with dietary intake and immune cells. Different mycobiome profiles, defined as mycotypes, were associated with different bacterial abundances.

My Honors Thesis is an extension of that paper. I focused on the technical aspects of the data analysis and critique of these methods – methods like PCA, clustering, and linear correlations. I covered computational topics such as dimensional reduction, data normalization, and applications of linear algebra and statistics. To better illustrate these algorithms, I showed them on a small subsample of the data, then on the complete set. I described how to interpret and justify the data models in the framework of ecology, biology, and statistics. Bioinformatic analysis will improve our understanding of the complicated microbiome and its interactions with the host.

Arnav Sharma

Major: Physiology & Neurobiology

Minor: Bioinformatics

Student Bio: Arnav Sharma went to high school at Westford Academy in Westford, MA. He is currently a third-year at the University of Connecticut, with a major in Physiology & Neurobiology and a minor in Bioinformatics. In his free time, he likes to spend time with his younger brother, watch TV shows, and play pick-up basketball.

Title of Thesis: Exploring the Frontiers of Nanopore Sequencing in Food Safety

With the advent of metagenomics, the ability to rapidly sequence and identify microflora has become a potential avenue of advancement in food safety. In my review, the first in its area, I take a look at advancements in Oxford Nanopore Technologies' Nanopore Sequencing techniques and analyze their applicability to food safety. Through this paper, I aim to analyze how ONT can build off the capabilities of Illumina's current NextGen sequencing technique with added benefits, such as cost-reduction, portability, long-read sequencing, and real-time data collection. I aim to acknowledge how ONT has demonstrated the ability to analyze microbiome, phylogenetics, anti-microbial resistance, etc. Additionally, I will discuss the areas in which ONT can be optimized to demonstrate industrial viability in the future.

Mehak Sharma

Major: Doctor of Pharmacy

Student Bio: Mehak Sharma will be graduating with her Pharm.D. degree in May 2022. Mehak is excited to join the pharmaceutical industry after graduation and will pursue a PharmD fellowship role in medical affairs. She has had several immersive field experiences in addition to her didactic courses at the School of Pharmacy. Being exposed to several career paths early on allowed Mehak to find her passion: utilizing scientific communications and medical information to help educate healthcare providers regarding novel treatment options for patients.

Title of Thesis: A Narrative Review: Pharmacy Intervention Fidelity

There has been a significant increase in the literature surrounding community-based pharmacy interventions. However, less is known about how researchers assured these interventions were implemented consistently and faithfully to the established protocol. This thesis is a narrative review which aims to describe the nature and extent to which researchers reported intervention fidelity measures across depression and hypertension studies completed in community and ambulatory care settings. For the methodology of this review, two research assistants used defined literature search criteria to identify manuscripts involving community pharmacist interventions in hypertension or depression care management. These research assistants independently evaluated each manuscript based on the nature and extent to which the studies described intervention training to support intervention fidelity, the intervention structure and content, the tools used to document intervention fidelity, and the extent to which the intervention was carried out as expected. Manuscript authors were contacted for clarification of any details not clear from their published works. Ultimately, results showed considerable variability in the nature and extent to which intervention fidelity measures are reported in the literature. Based on this preliminary review, researchers should be required to report key intervention fidelity measures when seeking publication of their research. Such additional reporting of fidelity results will enable the scientific community to have greater confidence in study results, conclusions, and implications.

Daniel Simmons

Major: Mechanical Engineering

Minor: Mathematics and Computer Science

Student Bio: I am an engineering student from Danbury, Connecticut. My first engineering experience was participating in a robotics team in high school; the engineering and teamwork principles I learned there inspire me to this day. My time at UConn has been filled with many more wonderful opportunities and experiences from the School of Engineering and the Honors Program. The clubs I have been a member of, such as Concrete Canoe and Formula SAE, have provided me with even more friends and engineering knowledge. I have also been an active member of Professor Norato’s research group, the Structural Optimization Laboratory, where I have studied topology optimization. I have been working with Professor Norato and his graduate student Hollis Smith for my Honors Thesis. My interests include computer-aided design and analysis.

Title of Thesis: Additive Manufacturing and Mechanical Evaluation of Fiber-Reinforced Structures

The goal of this project is to fabricate and evaluate the strength of 3D printed, fiber-reinforced structures whose designs have been obtained employing topology optimization techniques. The designs were optimized to maintain strength while minimizing the amount of material in the structures.

To test the mechanical properties for these structures, I physically produced and tested these designs and evaluated the degree to which their mechanical performance agrees with the finite element simulation of topology optimization used to generate them. Designs were printed using carbon filament with carbon fiber infill with a 3D printer. The prints were subjected to three point bending tensile tests in the Institute of Material Science. To do this, I placed a midpoint bending beam under a pneumatic press and increased the force applied until failure. This test produced the force-displacement curve of the structures from which the bending modulus can be found. The bending modulus represents the strength of the beam. The experimental value is directly compared to the predicted value to evaluate the accuracy of the model.

These structures can be constructed from multiple segments; this allows for the carbon fiber filament to lay upon multiple planes within the structure. Segmented construction could also be implemented in procedural manufacturing to support larger additive builds.

The flexibility of additive manufacturing compliments the unique designs produced by topology optimization, resulting in extremely strong and lightweight structures to meet the given parameters of any problem, which is why the samples were fabricated in this way. These topological principles and optimization parameters were designed for the parameters of the testing equipment, but can be applied to a multitude of load-bearing structures.

Aditi Sirsikar


Major: Physiology & Neurobiology

Student Bio: I'm a STEM Scholar from Acton, MA majoring in Physiology and Neurobiology. I worked in Dr. Eigsti's lab studying the efficacy of mental health screening tools for people with autism. In my spare time, I enjoy hiking and cooking healthier versions of comfort foods.

Title of Thesis: Screening for Depression in Young Adults with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition that is characterized by increased symptoms of depression, and depression in ASD is significantly underdiagnosed. High rates of undetected depression in ASD could suggest that the comorbid presentation of depression is unique, that there is somewhat reduced insight into symptoms, or that screening tools fail to capture critical symptoms in ASD.

In this study, we tested the convergence of self-and parent-reported symptoms of depression in young adults with ASD, as compared to an age-matched typically developing (TD) university sample. We tested whether the ASD group had differential reporting of physical versus emotional depression symptoms. Exploratory analyses tested the effects of gender on convergence.

Young adults with ASD reported significantly more symptoms of depression compared to their TD peers, consistent with findings that autism severity is associated with loneliness and depression. Alexithymia, characterized by difficulty recognizing emotions from internal bodily states, is frequent in ASD, and prompted an examination of whether somatic symptoms might be more readily reported in our ASD sample. However, both groups reported more somatic than affective symptoms, with no group difference. Strong parent-child concordance for both ASD and TD groups was consistent with prior work (Ozsivadjian et al., 2014). While women with autism, particularly those with cognitive abilities in the typical range, are often misdiagnosed, and might be expected to camouflage symptoms, findings suggest similar parent-child concordance in males and females. Overall, the current results suggest that the BDI-II may be adequate for probing depression symptoms in ASD.

Shreya Sreenivas

Major: Physiology and Neurobiology

Minor: Computer Science

Student Bio: Shreya Sreenivas, from Princeton, NJ, is a senior majoring in Physiology and Neurobiology and minoring in Computer Science. Throughout her time at the University, she has been heavily involved with research, the competitive synthetic biology team (iGEM), and serving on the CLAS Student Leadership Board. Her senior thesis looks at understanding the research approaches when it comes to studying emotional well being, and use a co-occurrence analysis to investigate neural mechanisms surrounding emotional well-being terms. Post graduation, Shreya has plans to work in tech consulting while completing her Masters in Statistics and Data Science at Harvard University. In her free time, she enjoys hiking, reading, and spending time with friends.

Title of Thesis: Using Co-occurrence Analysis to Explain How Researchers Study Emotional Well-Being

Psychological scientists have amassed a venerable body of research investigating negative psychological processes like distorted cognitive styles, stress, and negative affect (Alloy, Reilly Harrington, Fresco, Whitehouse, & Zechmeister, 1999; Reilly Harrington, Alloy, Fresco, & Whitehouse, 1999; Watson & Clark, 1995). These processes are crucial for better understanding of their role in the development and maintenance of nearly all of the mental disorders defined in the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 2000). Despite many decades of inquiry into well-being, much remains unknown. The study of well-being has evolved over time, shifting in focus and methodology. Many recent investigations into well-being have taken a neuroscientific approach to try to bolster understanding of this complex construct. A growing body of literature has directly examined the association between well-being and the brain. In this paper, we will attempt to understand the research approaches when it comes to studying emotional well being, and use a co-occurrence analysis to understand neural mechanisms used to study emotional well-being.

Bradley Stutzman

Major:Chemical and Biomolecular Engineering

Minor: Mathematics

Student Bio:My name is Bradley Stutzman and this May I will be graduating with a degree in Chemical and Biomolecular Engineering and minoring in Mathematics. Over the last four years, I have been involved in many different undergraduate research projects and clubs. To name a few, I am currently an undergraduate researcher for the Hybrid Modeling & Systems Engineering Laboratory, the president of Omega Chi Epsilon, a chemical engineering honors society, a teaching assistant for the introductory chemical engineering course, and a member of the Chem-E-Car club. Outside of school, I have participated in the REU (Research Experience for Undergraduates) program at WPI and worked with a startup company through the UConn TIPS Fellowship. In my free time, I enjoy reading, hanging out with friends, playing video games, and going to the gym.

Title of Thesis: Surrogate Modeling of Chemical Processes using Optimal Neural Network Structures

The focus of my thesis is modeling a chemical process using surrogate models. Chemical processes are made up of many complex unit operations that when multiple are put together in a process make the mathematical model complex and computationally heavy to calculate. In this case study, an ammonia synthesis process will be simplified using surrogate modeling. Surrogate models simplify these complex mathematical models into simplistic and computationally efficient mathematical models.

There are many different types of surrogate models. For this case study, the type of surrogate model used is a neural network. Neural networks have many hyperparameters that define the accuracy of the model. Some of the hyperparameters include the number of hidden layers, number of nodes in the hidden layer, type of node activation, etc. With a large number of hyperparameters, this leaves a large number of combinations of hyperparameters. There are no guidelines for how to set up the hyperparameters in a neural network structure to provide an accurate model for a given problem. So, it is impossible to hand-tune the neural network structure to find the most accurate model. With the use of hyperparameter optimization methods, the neural network structure is optimized to give the most accurate model based on the specified ranges of hyperparameters. I’m currently still working on investigating current hyperparameter optimization methods as well as experimenting with newer hyperparameter optimization techniques.

Nathan Wetherell

Major: Mechanical Engineering

Minor: Astrophysics

Student Bio: Nathan is a senior honors mechanical engineering student with a minor in astrophysics and a concentration in aerospace. He is an active member of the Engineering Peer Mentor program, which seeks to provide guidance in academic and professional areas for undergraduate and prospective engineering students. In his junior year, Nathan chose to further his investigation of his interests in aerospace, computer science, and astrophysics with an independent research project through the University Scholar Program. He will continue to combine his varied engineering interests at Pratt and Whitney as a member of the Manufacturing Engineering Development Program. After this program, he plans to continue his education by pursuing a master's degree in mechanical engineering.

Title of Thesis: Optimization of Orbital Trajectories Using NeuroEvolution of Augmenting Topologies

When looking for the best way to reach other planets, several different methods are used to determine the best path to take. One of the most popular is to use a simple Hohmann transfer, where the craft will be sent on an elliptical transfer between two circular orbits. However, this comes with its downsides, with a Hohmann transfer window to Mars only coming around every 26 months and taking 9 months to complete. My research looked at how neural networks can be used to try and optimize a transfer between two bodies given different parameter weights. Neural networks are computer models that seek to mimic a nervous system to convert input data into output actions. More specifically, I used a special scheme of neural network evolution called NEAT (neural evolution of augmenting topologies), where a genetic algorithm evolves the shape of the neural network itself over time to best solve the problem. I chose to use an Earth-Mars transfer for a case study and used the Hohmann transfer as a control. Inside a gravitational interaction simulation called an n-body simulation that I created, I generated the control Hohmann transfer orbit and allowed the neural networks to evolve given different parameter weights. The main parameters of interest were transfer time and fuel usage, though several different training parameters were also added. The training was divided into three main schemes, the first optimizing for time, the second optimizing for fuel usage, and the third optimizing for both. It was found that the neural networks were able to find more time-optimized transfers than the control while they fell behind in the fuel optimization cases. Overall, the neural networks were effective in determining orbital transfers between celestial bodies and optimizing for a given parameter. Future exploration of this concept would revolve around longer evolutions and array training across several different transfer windows.

Eric Zeiberg

Major: Biomedical Engineering

Minor: Mathematics

Student Bio: Eric is a senior Biomedical Engineering student on the Biomechanics track. Additionally, he is pursuing a minor in Mathematics. A member of the Honors program and the STEM Scholars program, he has a great passion for science and specifically the intersection of biology, medicine and computer science where he can leverage his software engineering skill set. His senior thesis has allowed him to work on a wide variety of issues such as 3D modeling, anatomical research, and various types of mechanical testing, and he enjoys learning about new areas of biomedical research. Eric spends his free time as a member of the Club Running team at UConn and as lead alto saxophone in the UConn Jazz Ensemble.

Title of Thesis: 3D Esophageal Model for Testing Novel Surgical Stapling Technology

Medtronic’s Product Development (PD) team is currently working on launching a new generation of Tri-Staple EEA Orvil device, a surgical device that offers a method for removing a tumor in the esophagus. The company’s Voice of Client team has completed interviews with surgeons and anesthesiologists to determine what changes needed to be made for this new product generation. However, an anatomically accurate esophageal model is required to test and establish specifications for the device, along with the potential impact of those changes on patient safety. Currently, there is no animal substitute that functions as an acceptable model for human esophageal anatomy, which makes it difficult for the PD team to move forward in the development and testing of the device. The objective of this project is to create a physical esophageal model using synthetic and 3D printed materials which the Product Development (PD) team could utilize to test and establish specifications for Tri-Staple EEA™ Orvil. This model will have similar dimensions to a statistically representative human and similar mechanical properties to human tissue.

Garrett Zeilinger

Major: Electrical Engineering

Minor: Mathematics

Student Bio: I am a graduating senior in the School of Engineering, majoring in electrical engineering with a concentration in Naval Science and Technology, and minoring in mathematics. My current areas of interest include systems control and automation, which I will pursue post-graduation by working as a systems engineer at General Dynamics Electric Boat in New London, Connecticut. However, I am from Martha's Vineyard, Massachusetts. I've lived there for roughly 15 years and have many great memories of living on a "vacation" island, although it's much more than that to me. Growing up on the water has inspired my interests within the naval and maritime industry, and is a major reason why I enrolled in the Navy STEM program here at UConn. I enjoy problem solving and learning new things, which lead me toward engineering. I also like to workout, read, cook, listen to music, and hang out with friends.

Title of Thesis: Viability of Bidirectional Wireless Power Transfer with Application to Unmanned Underwater Vehicle Battery Systems

The project objective was to design and demonstrate a system capable of bidirectional power transfer, done so wirelessly while submerged underwater. The ability to recharge and discharge battery systems in unmanned underwater vehicles (UUVs) is of continued interest within the naval industry. Because current industry practice requires surfacing a vehicle and physically accessing the battery compartment for charging or discharging, the development of a contactless system is preferred. Advantages of wireless charging for UUVs include reducing exposure to salt water and minimizing corrosion risks, decreasing the frequency of reconnections with a wired connection (i.e. physical strain on a connector), and automation of the charging process. To accomplish this, a symmetric circuit design was used, which would allow bidirectional capability. This enabled a battery load to either be in a charging or discharging state, depending on the direction of current flow. The use of a full bridge circuit on both the primary and secondary side provided the functionality of inverting or rectifying the signal to be transmitted over two inductively coupled coils. Within each full bridge were four MOSFETs (metal oxide semiconductor field effect transistors), driven by two complementary PWM (pulse width modulation) signals. These were produced by microcontrollers, which were used not only for the timing of switching actions (PWM signals to the MOSFETs), but also for data communication, including charge status and mode of operation (i.e. to control the direction of current flow to charge or discharge the battery load). The key focus of this project was on the command and control of bidirectional power transfer across a water gap, with application to vehicle battery systems. Future work could include implementation on an underwater docking station platform, and additional safety features for emergency shutoff.


Land Acknowledgment: We would like to acknowledge that the land on which the University of Connecticut is home to is the territory of the Mohegan, Mashantucket Pequot, Eastern Pequot, Schaghticoke, Golden Hill Paugussett, Nipmuc, and Lenape Peoples, who have stewarded this land throughout the generations.  We thank them for their strength and resilience in protecting this land and aspire to uphold our responsibilities according to their example.

To our [STEM Scholar] Seniors: Thank you for all your unique contributions and for your role in building and strengthening the STEM Scholar community through your undergraduate years. We will miss you, but we also take pride in your accomplishments as leaders and academics. We are proud to see your growth from consumers of knowledge to producers of knowledge, and we know that there is so much in store for you. Best of luck in the future and please keep in touch!

To those who support our Seniors: Whether you are a thesis supervisor, faculty member, family member, or fellow STEM Scholar student, we thank you for joining us in celebrating our STEM Scholars. While you are here, we encourage you to take some time to browse and explore just how much our graduates have accomplished!