YSP Alumni

Alumni Directory

2023 YSP Program Coordinators:
Claire Stipp and Yassine Souabny


2023 Video


 

Participating Labs

LabYSP StudentsTitleAbstract
Faculty:
Alam, Noor

Mentors:
Tianyu Yang,
Sahil Shikalgar
Mateo Ashton Jaramillo,
Angelina Le
Investigating the Impact of Self-Help Groups on Treatment Completion for Adolescents

Presentation
Poster
The Opioid epidemic is an ever-rising healthcare issue in the United States of America. Alongside the stigma associated with prescribing adolescents medicated treatment for OUD, the information we have on OUD treatment for adolescents is limited. But it is hypothesized that the success rate of treatment completion will rise with the normalization of medication in the patient's treatment plan. This study will assess the effectiveness of self-help groups and medicated treatments for adolescents suffering with Opioid Use Disorder (OUD), as well as compare the two to see if there exists a causal relationship to treatment completion. Methods: Using the Substance Abuse and Mental Health Services Administration’s (SAMSHA) discharge data from 2015-2019, the data was filtered for adolescents suffering from OUD, treatment modality, and other relevant information. The information was then organized into a demographics table. Moving on, various statistical methods will be used to assess the meaning of our data, such as the logistic regression model. That will be used in predicting the completion for different treatment modalities. From here we hope to formulate a causal conclusion for the effectiveness of self-help groups versus medical treatment for OUD using the average treatment effect on treated. This will also leave room for further research and discussion as to whether the two treatment types together are more effective compared to when they are administered separately.
Faculty:
Amini, Rouzbeh

Mentor:
Turner Jennings
Michael Marchev,
Dmitra Mukasa
Head/Helmet Contact Force Characterization in Combat Helmet Systems

Presentation
Poster
Current combat helmets consist of an exterior fiber composite shell followed by an interior soft foam padding. This foam layer provides additional protection by absorbing shock transferred from helmet shell to skull through compression upon impact. Existing research does not consider precompression that occurs while wearing the helmet; the accuracy of these models used to model force propagation is therefore limited. This affects predictions of the risk of impact-induced traumatic brain injuries. Four different size helmets have been instrumented with contact pressure sensors on the interior padding system. We will use these instrumented helmets to measure head-helmet interface contact forces on volunteer users. We hypothesize that interface forces will change depending on whether the user fastens the helmet strap and that male and female volunteers will additionally contrast due to statistical differences in head size. The experiments conducted will be used to calibrate finite element simulations of impacts on a helmeted head to develop higher-performing energy absorbing materials capable of reducing the risk of impact-induced traumatic brain injury.
Faculty:
Amirabadi, Mahshid

Mentor:
Mojtaba Salehi
Eleanor Palmer,
Abigail Wojtaszek
Developing a Linear DC-DC Converter for Solar Powered Phone Chargers

Presentation
Poster
Renewable energy sources create an opportunity to decrease the use of fossil fuels and provide a sustainable way to power the grid. The sun is a consistent source of energy for the planet, and photovoltaic (PV) panels use that energy to supply different loads in a clean way. However, for the photovoltaic panel to sustainably charge a battery, it needs a converter to change DC voltage to a different amplitude DC voltage. For our project, we developed a linear converter to use the energy generated from a photovoltaic panel to charge a Li-ion phone battery. We simulated our design using PSIM software, where we also tested factors such as different irradiation level and temperature, and variable loads to find the ideal conditions for maximized output power. The goal of the project is to develop a clean and accessible phone charger that functions in various locations.
Faculty:
Dong, Sijia

Mentors:
Zheyu Zhang,
Gustavo Mondragon
Julia Chen,
Annie Stone-Peterson
Computational Photoenzyme Discovery and Design

Presentation
Poster
Enzymes are proteins that function as catalysts to accelerate chemical reactions by lowering the required activation energy. Cofactors, also known as “helper molecules”, are non-protein chemicals that bind to enzymes and serve a critical role in helping them carry out their functions. For this project, we focused on a group of photoenzymes extracted from the Protein Data Bank (PDB) that either contain the cofactor FMN or NAD. The objective was to determine the substrates of these photoenzymes and to create a new database for the photoenzymes that were found to include more than one cofactor. This would then foster a better understanding of enzyme catalysis and molecular interactions. This data, collected on a spreadsheet, will then be published as a database on an educational platform to disseminate the information for others to view and use. Such data would be essential for students to have a better understanding of the specific reactions and interactions that these specific enzymes can perform and for researchers working in the drug delivery or biomedicine field.
Faculty:
Koppes, Ryan

Mentors:
Nolan Burson,
Katherine Nilov,
Bryan Schellberg
Kyle Denny,
Cooper Love
Next Generation Organ on Chip Platforms

Presentation
Poster
Organ on chip platforms are used to investigate and answer biological questions. Cells are cultured into these devices, which model human organs. These chips are used by researchers as tools to more accurately mimic biological functions and their processes in vitro. For example, intestinal cells cultured on the chip mimic the organ’s barrier function and regulate the diffusion of nutrients. This project’s goal is to measure and compare the diffusion of particles across a membrane, which is similar to the intestinal barrier, using varied geometries. We will achieve our goal using the laser cut and assembly method to produce chips layer by layer with unique geometries. The chips will then be assembled and flow tested using a syringe pump. Flow data will be collected to analyze the effect of chip geometry on diffusion rates. The newer designs will be compared to control designs that are previously published. Our preliminary testing may give a better understanding of how diffusion occurs in organ chips, which can help with better predictive models of processes in the human body. In the future, this will enable engineers to create improved chips that can eventually be used for pre-clinical testing.
Faculty:
Oakes, Jessica

Mentors:
Jackie Matz,
Matthew Edan,
Hannah Kim
Yosef Elbehisy,
Lucca Valdes
Evaluating Lung Function Changes with Environmental Exposures

Presentation
Poster
The overall objective of this study was to investigate the effects of aerosol exposure on the respiratory system of mice, specifically the biological underpinnings of disease progression. High-resolution computed tomography (CT) imaging data was employed to generate comprehensive 3D models, enabling thorough analysis of structural changes, revealing the nasal cavities to be normal and undamaged. This 3D model will be utilized in the future to predict aerosol dosimetry, needed for experimental planning purposes. Increases in smooth muscle tissue results may result from exposure, notably leading to reduced lung function and morphological changes within the respiratory tract. Here, we utilized image-J analysis software to measure and evaluate mean intensities of smooth muscle tissue and epithelial cell mass in the airways of mice exposed to JUUL e-cigarettes for 8, 16, and 24 weeks. The data concluded that there was an initial statistically significant increase in smooth muscle signal intensity at 8 and 16 weeks of e-cigarette exposure and that effect wore off over time, as was evident in the data gathered from the 24-week exposure group. We hypothesize that the exposed mice acclimated to the e-cigarette exposure, leading to a decline in smooth muscle activity in comparison to the initial increase.
Faculty:
Onabajo, Marvin

Mentors:
Thomas Gourousis,
Minghan Liu,
Yunfan Gao
Alexis Chen,
Brendan O'Riordan
Programmable Signal Acquisition and Calibration of Temperature Sensors for Detection of Power Dissipation on Chips

Presentation
Poster
Integrated circuits on chips for wireless communication and computing applications dissipate power, which changes the temperature of the nearby silicon area. This temperature change can be monitored with on-chip temperature sensors to detect faulty operation as well as malware. The overall goal of this research is to create design techniques that allow the detection of abnormal operation of chips for Internet of Things (IoT) devices using on-chip temperature sensors and off-chip machine learning methods. As a step towards achieving this goal, this summer's research project will include the development of a measurement setup to automate the calibration of temperature sensor circuits.
Faculty:
Ostadabbas, Sarah

Mentors:
Elaheh Hatami,
Pooria Daneshvar Kakhaki, Xiaofei Huang
Victoria Berry,
Franklin Chen
Computer Vision and its Applications in Infant Health Monitoring

Presentation
Poster
In the United States, approximately seven percent of children are affected by neurodevelopmental delays; however, only about a third of children under the age of five receive recommended developmental screenings. This delayed screening can impact children who are at risk for neurodevelopmental delays—congenital torticollis, autism spectrum disorder, cerebral palsy, etc.—not to receive the proper support and have more difficulties in academics, social interactions, and other long-term developments. This research project aims to develop a monitoring device able to provide developmental screenings and detect abnormalities in infants using computer vision and artificial intelligence. Data was gathered and processed from raw footage of infants naturally interacting with their environments, then fed to machine learning models to learn the representations of motor functions. Large quantities of short clips showing infants performing certain motor functions, and images during peak action were extracted from longer home videos to serve as a benchmark for training the infant action recognition models. The infants' actions were separated into several categories, including holding, reaching, and grabbing. Additionally, the raw home videos had been annotated for the different motor functions displayed. Infant pose and joint coordinates were estimated using MediaPipe Pose onto the images as low-dimensional representations for the machine learning models. The skeleton-based representations provide researchers and computer vision models a better understanding of typical infant motor functions and will be fed to deep neural networks to automatically detect infant abnormalities.
Faculty:
Shefelbine, Sandra

Mentors:
Vineel Kondiboyina,
Soha Ben Tahar
Max Bean-Tierney,
Ananya Katyal
Gait Force Assessment and Analysis

Presentation
Poster
The knee modeling study seeks to determine the efficacy of physical therapy in alleviating knee arthritis pain through a comprehensive gait force analysis. Despite previous research on knee joint forces, there remains a significant gap in knowledge around the physiological mechanisms associated with physical therapy. To address this, we used a musculoskeletal model created using Visual3D and OpenSim software to calculate load distribution on various muscle groups through the gait cycle. Data was processed and graphed using an automated MATLAB program, which allowed for careful investigation of force distributions during gait and allowed us to evaluate the effect of physical therapy. 300 data points were analyzed per trial, yielding independent graphs of total force exerted on the knee across five trials, in addition to individual graphs for the medial and lateral muscle groups. Comparing the newly generated graphs against pre-physical therapy knee force graphs provided us insight on the effectiveness of physical therapy in reducing and redistributing musculoskeletal load during gait for knee arthritis patients. These findings point to potential benefits of physical therapy in alleviating harmful gait abnormalities associated with knee arthritis. This provides us with a more comprehensive understanding of the physiological elements that govern the benefits of physical therapy.
Faculty:
Shrivastava, Aatmesh

Mentors:
Kayland Harrison,
Kaden Du
Ethan Andersson,
Zaraius Bilimoria
Circuit as a Puzzle Game

Presentation
Poster
Designing circuits in electrical engineering can be a challenging task. To make the process more accessible and engaging, we have created a web-based game. This game allows users to solve pre-made circuit puzzles by finding missing values. These levels leverage Kirchhoff's current and voltage laws and help the user develop their circuit solving skills. Advanced levels will be more open-ended and allow the user to make more creative solutions. Additionally, users can design their own circuits and solve for various unknowns. The game serves as an educational tool, introducing students to circuit concepts and encouraging independent exploration. The game is being developed using JavaScript and incorporates user-friendly tools like PIXI.js for circuit component placement and PySpice for solving circuit values.
Faculty:
Willits, Rebecca

Mentor:
Rachel Shovmer
Alexandra Cajiga,
Neil Patel
The Impact of Blocking Buffers on Brain Immunohistochemistry

Presentation
Poster
Immunohistochemistry is a tool used for labeling proteins present in a tissue sample. When visualizing proteins, one problem that arises is that there is cross reactivity of markers—or antibodies. The goal of this project is to optimize different blocking buffers to stop cross reactivity of the antibodies. We will use different concentrations of BSA, Triton, and Donkey serum as blockers to stain tissue. After the samples are stained, the tissues will go under a microscope that will illuminate the proteins. We hope to find the best combination of blockers and surfactants that will isolate our targeted proteins. Solving this problem will help the lab with future staining work, as they stain for proteins relating to glaucoma.