Team 1

Eugene Hwang, Hyewon Yoo,

Saerin Nam

Track: Public Health

OralCare: A Microbiome-Aware Digital Platform for Optimizing Oral Health and Nitric Oxide Bioavailability

Oral health is a critical yet often overlooked determinant of systemic health, particularly through its role in regulating nitric oxide (NO) bioavailability via the oral microbiome. Despite widespread awareness of oral hygiene, adherence to preventive behaviors remains inconsistent, limiting its potential health impact. We propose OralCare, a behavior-driven digital platform that integrates microbiome-informed guidance, habit tracking, and dentist-supported care to improve oral hygiene adherence and support systemic health outcomes.

Team 2

Jeongwoo Lee, Dow Kim, Yuna Komurasaki, Jennie Kang

Track: Therapy and treatment

Hormonal Regulations in Dysmenorrhea

Polycystic Ovary Syndrome (PCOS) is a prevalent condition driving secondary dysmenorrhea, characterized by a chronic intra-ovarian hormonal imbalance where deficient aromatase activity leads to toxic androgen accumulation and a critical shortage of estrogen. Current clinical treatments, such as hormonal contraceptives and metformin, primarily offer symptom-based relief without directly addressing the underlying enzymatic defects. This study proposes a mechanistic approach to rehabilitate the natural steroidogenic pathway by inducing aromatase (CYP19A1) expression. Utilizing KGN human granulosa-like cells exposed to excess testosterone and insulin to mimic PCOS conditions, we transfected cells with a CYP19A1 plasmid to test its efficacy alone and in combination with metformin. Preliminary results suggest that while CYP19A1 overexpression moderately restores hormonal balance, the combination treatment yields the strongest restorative effect on estrogen production.

Team 4

Megan Hoang

Track: Biomedical engineering

Gradient Drug Resistance Chip: 3D Tumor-on-a-Chip Platform for Modeling Spatial Drug Exposure

Tumor resistance to chemotherapy and cancer targeting drug treatments is driven in part by spatial differences in drug exposure within the tumor microenvironment, a feature poorly replicated in traditional two-dimensional models. This proposal proposes a model for a microfluidic chip that generates controlled drug concentration gradients across a hydrogel-based 3D tumor model. This system enables visualization and analysis of how heterogeneous drug distribution contributes to differential treatments response and resistance in cancer therapies.

Team 5

Diya Madhavan, Reva Diwan

Track: Mechanisms (Molecular, cellular, systems biology)

Alzheimers Drug Candidate Selection

This project presents a patient-facing Alzheimer’s treatment advisor that gives you a personalized drug recommendation based on disease stage, biomarker status, treatment goals, and monitoring preferences. It combines rule-based ranking with explainable, DBR-X–inspired pathway visualizations to provide both accessible summaries about other in-process Alzheimer’s drugs that are currently up and coming and clinician-oriented insights which can be accessed under the more information button. The platform also integrates clinical trial matching, aiming to bridge decision-making between patients and providers while increasing transparency and trust in treatment selection.

Team 10

Hera Ohannessian, Lilia Hacoupian, Jay Ann Kan, Talin Dergevorkian

Track: Public Health

The 28 Bar: Nutritional Support for Menstrual Health

The 28 Bar is a protein bar designed to support women during their menstrual cycle. As progesterone levels drop before menstruation, women can experience changes in their immune system and increased cravings. The 28 Bar not only provides a source of protein but it also satisfies these cravings, making it a convenient and comfortable option during this phase.

Team 11

Clarissa Lai, Peter Soliman,

Ayesha Mirza, Harris Kiaris

Track: Mechanisms (Molecular, cellular, systems biology)

The Rodent Race: Comparative Genomics for Optimal Model Organism Selection

This project compares exon-level sequence homology between human and each of the two primary rodent models (Mus musculus and Rattus norvegicus) across gene signatures relevant to specific organs and diseases. The goal is to produce a tissue-by-tissue scorecard indicating which rodent more closely mirrors human genomic architecture for each biological context of interest.

Team 14

Sahana Chowlur, Lipika Goel, Harshita Kukreja, Caitlin Nguyen

Track: Biomedical engineering

Optimizing solutions for chronic dry eye through thermal-based therapies

Given the prevalence of dry-eye disease worldwide, it is necessary to find a treatment that is affordable and convenient to the average consumer. We are developing a novel sleeping mask that provides warmth and a gentle pulsation motion against the eyelid, thus stimulating the oil glands in the eyelid to lubricate tears and therefore treating evaporative dry eye condition.

Team 17

Barkha Trivedi, Purvi Vijayprakash

Track: Biomedical engineering

HealSync: A Smart Bandage with Digital Twin and Real-Time Doctor Monitoring for Predictive Wound Healing

HealSync is a smart wound healing platform that integrates a bioelectronic bandage with a mobile application and clinician dashboard for real-time monitoring. The system tracks key biomarkers such as pH, temperature, uric acid, and healing progression, using statistical algorithms to analyze trends and identify potential complications. By visualizing wound data for both patients and clinicians, HealSync enables earlier detection of infection risk and more informed clinical decision-making.

Team 19

Jaiden Ha, Arzoo Virani,

Geethika Tammana

Track: Therapy and treatment

A comparative analysis of type 2 diabetes treatments to build a precision medicine predictive model

Type 2 diabetes is becoming increasingly prevalent in the United States, and it is associated with a diverse range of risk factors and symptoms. Several classes of treatments currently exist for Type 2 diabetes, including GLP-1 receptor agonists, SGLT2 inhibitors, and Metformin. This research project aims to utilize existing data on each of these treatment’s impacts on various biological criteria to build a predictive model, helping determine which treatment is most effective in treating Type 2 diabetes.

Team 21

Nadia Tsai, Eason Luo,

Benjamin Davis

Track: Mechanisms (Molecular, cellular, systems biology)

Identification of a Minimal and Robust Transcriptomic Signature for Classifying APP/PS1 and Wild-Type Mice in Early Alzheimer’s-Associated Vascular Dysfunction

This project intends to leverage transcriptomic data from APP/PS1 Alzheimer’s model mice as reported by Noah Schweitzer’s et al. in “Linking cross-species trajectories of cerebrovascular remodeling in aging and Alzheimer’s disease to brain vessel transcriptome” (bioRxiv, 2026) to identify early cerebrovascular molecular changes that occur prior to overt amyloid plaque formation. By comparing gene expression profiles between APP/PS1 and wild-type mice, the study aims to uncover signatures of vascular dysfunction, including inflammation, angiogenesis, and blood-brain barrier breakdown. These findings may support the development of predictive models for early Alzheimer’s disease and improve understanding of vascular contributions to neurodegeneration.

Team 22

Guthrie Shea, Margo Azzam

Track: Mechanisms (Molecular, cellular, systems biology)

Uncovering the Pathways of Alzheimer’s Disease Progression through Human Herpesvirus 6 Mechanisms

This study hopes to peer into the interactions between Human Herpesvirus 6 (HHV6) and Alzheimer’s Disease (AD). Through the comparison of amyloid beta accumulation in cells with knockouts in ApoE and TREM2, we hope to see whether subsequent HHV6 infection impacts these lines differently. These results would provide insight into the interactions between HHV6 and ApoE/TREM2 pathways, and whether they are ultimately responsible for neurodegeneration associated with HHV6 infection.

Team 23

Erica Cho, Jaelyn Han, Sangyun Han

Track: Therapy and treatment

From Gut to Skin: ULIPSTIC Mapping of Microbiome-Induced Antigen-Specific T Cell Interactions Reveals Mechanisms of Inflammation in Atopic Dermatitis

The skin, the largest organ in the human body, is colonized by a wide variety of microorganisms that play essential roles in maintaining immune homeostasis. Atopic Dermatitis (AD) is one example where this microbial ecosystem is disrupted in the skin barrier, often with the overgrowth of the pathogen Staphylococcus aureus (S. aureus) that worsens chronic inflammation and disease progression. This study proposes to use a two-step treatment of an antiseptic pre-treatment followed by the application of engineered skin commensal bacteria Staphylococcus epidermidis (S.epidermidis) to induce anti-inflammatory responses, offering a new microbiome-based approach to treating AD.

Team 24

Ashley Kim, Diane Lee, Audrey Choi, Juhyeong Lee

Track: Therapy and treatment

Immune Escape Detector: a tool that flags tumor mutations likely to cause immune evasion

We propose the development of an Immune Escape Detector, a computational tool designed to identify mutations that may enable viral or tumor cells to evade immune recognition. Focusing on the Q129H mutation in the Hepatitis B surface antigen, this project aims to bridge the gap between mutation detection and functional interpretation. By prioritizing variants based on their impact on immune pathways, the tool could support research on immunotherapy response and disease progression.

Team 26

Maya Subramoni, Hannah Wawda, Ishita Puggera, Tanisha Pidshetti

Track: Biomedical Engineering

Flex Sensor Controlled Soft Robotic Hand for Medical Applications

Strokes can damage parts of the brain that control muscles and as a result, can impair hand movement. To address this issue, we aim to create a glove embedded with flex sensors and soft robotic actuators to emphasize the movement of the user. This will allow the user with rehabilitation, improving the rate of recovery. 

Team 27

Abdulmajeed Banjar, Sarah Alakkas, Mohammed Aljohani, Ola Alharbi

Track: Mechanisms (Molecular, cellular, systems biology)

Selective Disruption of Cumulative Memory in EHMT1-Associated Cognitive Dysfunction: A Behavioral and Mechanistic Framework

Memory is commonly treated as a single process, but recent behavioral paradigms suggest the existence of distinct subtypes, including cumulative memory, the ability to integrate information across repeated, overlapping experiences. This proposal investigates whether cumulative memory is selectively disrupted in EHMT1-associated cognitive dysfunction using the Object Space Task (OST) in wild-type and EHMT1-deficient mice. We introduce a novel Cumulative Memory Index (CMI) to quantify trial-level integration and propose a mechanistic framework linking cumulative memory to hippocampal reactivation dynamics.

Team 29

Catherine Xie, Britney Trieu, Bridget Vause, Aron Martin

Track: Therapy and treatment

Optimized mRNA-LNP Platform Enables Both Antigen Expression and Innate Immune Activation for Enhanced Cancer Immunotherapy

Inclusion of modifications in mRNA decreases exonuclease cleavage and sensing by various pattern receptors, creating “immunosilent” mRNA with increased translation efficiency, opening the door to mRNA as a vaccine platform for cancer treatment. However, the lack of immunogenicity necessary for a robust immune response is ineffective against immunosuppressive cancers. Our solution was to build and test an optimized RNA-LNP platform that is both recognized by pattern recognition receptors related to viral receptors to boost the immune response and still leads to antigen presentation. The optimized platform enables antigen expression and innate immune activation in which both components can be stimulated within a single vaccine. The findings from our project will offer insight for optimizing RNA vaccine formulation, which has the potential to be utilized for future cancer immunotherapies.

Team 31

Charles Victorio, Siyuan Qian, Natalia Patterson, Fatemah Mirza, Kayla Truong

Track: Biomedical engineering

Detecting E. coli in Water with DIY LAMP on a Chip

We are developing a low-cost, open-source microfluidic chip that uses loop-mediated isothermal amplification (LAMP) to detect Escherichia coli in water samples. By combining DIY-accessible photolithographic fabrication methods with isothermal nucleic acid amplification, our platform aims to deliver rapid, sensitive, and field-deployable pathogen detection suitable for

resource-limited settings where waterborne E. coli remains a leading cause of morbidity and mortality.

Team 32

Shuo Li, Nathan Wang

Track: Biomedical engineering

Bayesian Optimization of Microfluidic Organ-on-Chip Geometry for Wall Shear Stress Uniformity with Rapid Prototyping Validation

Organ-on-Chip (OoC) devices are precision microfluidic platforms that require carefully controlled fluid environments — in particular, uniform wall shear stress (WSS) across the cell culture surface — to reliably recapitulate in-vivo physiology. Current design practice relies on heuristic iteration and manual parameter tuning, leading to long feedback loops and inconsistent device performance. We address this by constructing an end-to-end automated pipeline that couples a parametric geometry generator, a high-fidelity computational fluid dynamics (CFD) solver, and a Bayesian optimization (BO) loop to systematically explore a five-dimensional continuous parameter space across eight discrete channel configurations. The optimizer minimizes the coefficient of variation of floor WSS subject to physiological shear and dead-zone constraints. The winning design is then fabricated via SLA 3D-printed molds and PDMS soft lithography, and validated against CFD predictions using food dye flow visualization and fluorescein washout residence-time distribution experiments. The deliverable is an open-source pipeline and a quantitative demonstration that the optimized chip achieves significantly more uniform shear stress than a naive baseline, closing the design-fabrication-validation loop in a reproducible and automated fashion.

Team 33

Emily Naiman, Marco Renteria

Track: Mechanisms (Molecular, cellular, systems biology)

Investigating Potential Markers for Early Metastasis of Ocular Cancer

Uveal melanoma is a rare but lethal intraocular malignancy with a 50% chance of metastasis primarily to the liver, and 92% of mortality following metastasis diagnosis. Current methods of screening involving biannual MRI scans of high risk patients fall short, as metastatic primed tumor cells can remain dormant for up to 40 years, and identification occurs after tumor pathology has already been established. This study proposes identifying immune pattern markers in the liver upon activation of dormant uveal melanoma cells as a means of flagging metastasis before progression and offering a framework for future developments in screening methods.

Team 34

Kavya Desai, Neha Adapala,

Kiersten Roth, Onyeka Idiaghe

Track: Therapy and treatment

Sex-Stratified Statin Toxicity Prediction: A Multi-Modal Machine Learning Approach Incorporating Hormonal Covariates

Women are systematically undertreated with statins due to poorly characterized sex-specific side effects, leaving cardiovascular disease and dyslipidemia mismanaged in a high-risk population. We develop a stacked ensemble model (XGBoost, LightGBM, Random Forest, and Logistic Regression with a meta-learning layer) trained on FAERS, NHANES, and PharmGKB data to predict individualized risk of myopathy, glucose intolerance, and hepatotoxicity given a woman’s hormonal status, statin type, and genetic profile. This enables clinicians to get individualized recommendations for patients while considering how their hormonal status impacts their risk in taking statins instead of using population averages derived mainly from male cohorts.

Team 35

Dev Pathak, Nupur Gupta

Track: Therapy and treatment

Detecting E. coli in Water with DIY LAMP on a Chip

Virtual reality exposure therapy (VRET) is a new tool that helps treat anxiety disorders, but current systems either require supervision or don’t have any sort of safety net built into them. We propose a reinforcement learning system that will take real time user feedback and adjust the levels of exposure given to the user. This makes VRET more accessible while also making sure that users are within a safe and manageable range during therapy.

Team 36

Yeonjun Kim, Ashley Do,

Caroline Kesler, Ayaan Mohammad

Track: Biomedical engineering

Rapid Single-Cell Cytokine Profiling for Early Sepsis Detection Using Nanovials

This project introduces a rapid, single-cell diagnostic platform for early sepsis detection using functionalized, picoliter-scale Nanovials (engineered test tubes). By capturing individual white blood cells and measuring IL-6 cytokine hypersecretion via a sandwich immunoassay, the platform addresses the inaccuracies of traditional detection methods. Integrated with custom image analysis software, this end-to-end solution aims to provide high sensitivity and specificity for clinical use in low-resource settings.

Team 37

Joy Szeto, Jessie Zeng, Jiaxun Hong

Track: Therapy and treatment

A non-invasive colorectal cancer diagnosis: investigating protein in blood as biomarkers for methylation/copy number alterations

Colorectal cancer is commonly diagnosed through invasive procedures such as biopsies and colonoscopy, highlighting the need for less invasive alternatives to enable more accessible and frequent screening as well as earlier detection. Using TCGA data, we investigated whether blood-based protein biomarkers reflect underlying DNA methylation and copy number alterations. Our findings suggest that gene expression patterns are associated with these genomic changes, highlighting their potential for non-invasive colorectal cancer detection.

Team 38

Adrian Bautista, Stephanie Gochuico

Track: Mechanisms (Molecular, cellular, systems biology)

PathogenShield: Antibiotic Resistance Prediction Dashboard

This project for the Biohackathon is a business proposal for the development of an antibiotic prediction model. By using AI and machine learning, we hope testing and development can be more efficient.

Team 40

Anya Varkey, Sreeja Dorepally

Track: Public Health

LunaLift- Integrating strength training, nutrition, and menstrual cycle insights for personalized, physiology-driven performance

This app is a centralized platform designed for health-conscious women who lift weights, integrating workout tracking, menstrual cycle syncing, and personalized nutrition in one place. By aligning training intensity, recovery, and dietary needs with hormonal
fluctuations, it provides evidence-based recommendations tailored to female physiology. The goal is to simplify complex variables into a seamless system that optimizes performance, health, and long-term consistency.

Team 42

Jade Finley, Maya Burli, Camryn Whitmore

Track: Public Health

Detection/Prediction of Cervical Cancer

Cervical cancer is a significant public health issue, especially
in low-income and resource-limited settings. The aim of this research is to develop an accessible, at-home alternative for cervical cancer screening that reduces dependence on clinical visits. This approach is expected to increase screening accessibility and participation, especially in underserved populations by providing a low cost, non- invasive, diagnostic option.

Team 43

Charissa Mak, Tammy L Sisodiya

Track: Biomedical engineering

Vasovision AI: Real-time CNN-based monitoring of vascular integrity and hemodynamics in organ-on-a-chip systems

VasoVision AI utilizes a ResNet-34 U-Net and temporal interpolation to transition from static imaging to predictive hemodynamic stress testing, identifying shatter points in network connectivity that precede total density loss. By integrating iPSC-derived digital twins and computational fluid dynamics, our framework simulates personalized drug-dose responses in silico to catch rare, unpredictable, and dose-independent adverse drug reactions before clinical intervention.

Team 44

Brianna Gianetto

Track: Mechanisms (Molecular, cellular, systems biology)

Development and Characterization of an Optimized Murine Model for Metastatic Prostate Cancer

This project aims to develop and compare murine models that better mimic metastatic prostate cancer by using PTEN-KRAS tumor cells and multiple injection strategies. The study tests how cell number, injection route and suspension medium affect tumor growth and spread, with PET-CT and tumor volume measurements used to assess model performance.

Team 45

Htet Khant, Kaung Hein, Shania Desai

Track: Mechanisms (Molecular, cellular, systems biology)

Conditional systemic JAK1 depletion affects periodontal inflammation and alveolar bone remodeling

COL1A1 effect on Dentin Wettability and Implications on Bonding systems: So we will be comparing Wild type mice group with Collagen knockout (COL1A1 KO) mice group, n~7, and then we will take their molar tooth, cut it in half and then we will measure dentin surface wettability using an optical tensiometer with distilled water and diiodomethane. Then we measure contact angles via sessile drop method and surface free energy will be calculated to compare changes in hydrophobicity vs hydrophilicity. The hypothesis is that knockout of collagen lowers hydrophilicity of the dentin matrix due to decrease in dentin collagen network that binds to water.

Team 47

Imaan Soltanalipour

Track: Biomedical engineering

CRISPI-CS: Closed-Loop Real-Time Imaging and Stimulation Pipeline Infrastructure for Compressive Sensing Neural Connectivity Mapping in iPSC-Derived Neural Tissue

CRISPI-CS is a platform integrating the Spatio-Temporal Illumination Microscope (STIMscope) open-source hardware system: including a digital micromirror device (DMD), IDS Peak camera, integrated control electronics, GPIO-driven excitation LEDs, specialized lenses, and a custom-built mount with a unified PyQt5 GUI deployed on an NVIDIA Jetson AGX Orin. The platform enables precise widefield imaging, fluorescence recording, patterned optogenetic stimulation, camera-projector calibration, real-time fluorescence trace extraction, an offline setup pipeline with agnostic segmentation algorithms, and a modular compressive sensing (CS) inference pipeline for mapping functional connectivity between neurons in iPSC-derived neural tissue to find synaptic interactions relevant to neurological disorders.

Team 49

Nathaniel Luna, Lindsay Cheng

Track: Biomedical engineering

Wearable EEG Monitoring as a Pre-Symptomatic Alzheimer’s Biomarker Tool in Systemic Vascular Disease Patients

Individuals with systemic vascular disease have been shown to have an increased risk for developing mild cognitive impairment (MCI) and Alzheimer’s Disease (AD), stemming from cerebrovascular dysfunction and cerebral hypoperfusion (reduced blood flow to the brain). There is a need for passive electroencephalography (EEG) monitoring, such as a wearable headband-like device, as a method of pre-symptomatic risk assessment and stratification. EEG monitoring provides specific coupled wave power ratios (alpha3/alpha2, theta/alpha, theta/gamma, beta/theta) that serve as biomarkers of neurodegeneration and cognitive decline, and are observable before symptom onset. Our research proposes a wearable EEG prototype designed for continuous and passive monitoring of the biomarker power ratios specifically intended for systemic vascular disease patients who carry a higher risk of developing cognitive impairment and conversion to AD. 

Team 50

Edward Bui

Track: Therapy and treatment

Targeted Suppression of LINE-1–Driven cGAS–STING Inflammatory Signaling in Senescent Cells

This proposal investigates whether senescence-associated inflammatory signaling can be reduced by targeting two mechanistic points within the senescence–LINE-1–cGAS/STING axis. Specifically, the project compares upstream suppression of LINE-1 activity through SIRT6 activation using MDL-800 with downstream inhibition of STING signaling using H-151, and tests whether combined intervention more effectively reduces interferon-associated SASP output and bystander DNA damage than either treatment alone.