The record
A selection of Fellow results, listed as they appear in each venue’s own index. Where a public record exists, follow the entry to the source and check it yourself.
Ruthwik D.METHI: An Ensemble-Based Machine-Learned Exoplanetary Habitability Index
Nidhi K.Skin Microbiome Signatures for Non-Invasive Detection of Autoimmune Disorders
Aditya S.Multi-Step Neural Anomaly Detection in Large-Scale Cloud Systems, Best Oral Presentation
Raeyaan M.Real-Time Control of a Low-Cost Robotic Arm Using EMG Signal Classification
Aarav B.Traffic Detection and Prediction for Intelligent Transportation Systems
Sai T.Automated Hybrid In-Situ River Remediation
Ishaan M.Waste-to-Resource Conversion
Karan A.Impact of Short-Duration Geopolitical Events on Indian Stock Market Returns, full paper accepted at an international finance symposium in Riga, Latvia
Aditya A.EEG Motor Imagery Signal Classification for Brain Computer Interfaces: A Comparative Analysis of Machine Learning and Deep Learning Models, accepted in Sydney, Australia
Suriya D.Eye-Tracking Signatures for Early Detection of Alzheimer's Disease
Ashwajit W.First-author Springer publication, presented in Merida, Mexico
Sai P.Genomic Surveillance of 132 Immune Escape Mutations in Omicron Variants
Diya A.Machine Learning Applications in Public Health Research
Atharv V.Published at an IEEE conference
Srihaan E.Published at an IEEE conferenceMeera R.Structure-Aware Computational Discovery of Gut Microbial Nitroreductases for Drug Metabolism, accepted at an IEEE conferenceElliot W.MRI-Guided Personalized Helmet Liner Design Toward Head-Injury Prevention, accepted in Glasgow, UK and published by Springer
Sadaf S.Built a venture on top of her Fellowship research and was selected for the WUHC Incubator Pitch Competition at Wharton
Mubashir S.ISEF 2026 qualifier, gravitational-wave ML pipeline, Best of Category at nationals
Jayant K.ISEF 2026 qualifier, low-resource CNN for gravitational-wave classification
Ansh K.Presented at the MIT Undergraduate Research Technology Conference
Avyay G.1st place, state qualifier, AI health prediction models
Aarush M.3rd place worldwide, 1 of 14 finalists from 8,000+ participantsA sample of the record, updated as results come in. Entries marked VERIFY AT SOURCE resolve on IEEE Xplore.
ALL CASE STUDIESThe research, in their own words
Every Fellow presents their work on camera at the end of the program. A few of the recent ones are below. Watch a fifteen-year-old walk through their own methodology: this is the part no brochure can fake.
Cancer-Aware Attention CNN for Acute Lymphoblastic Leukemia Subtype Classification
Built an attention-based convolutional neural network for classifying acute lymphoblastic leukemia subtypes from blood smear images, using cancer-aware attention to focus the model on diagnostically relevant cell features.
AI-Powered Multi-Omics for Climate-Resilient Crops
Integrated transcriptomic, genomic and machine learning methods to identify stress-tolerant genetic targets in crops, an AI-powered multi-omics approach to breeding for a changing climate.
OTFS vs OFDM for UAV Integrated Sensing and Communication
Compared OTFS and OFDM waveforms for integrated sensing and communication in UAV systems, evaluating which modulation scheme delivers better simultaneous radar sensing and data transmission in high-mobility drone environments.
AI Framework for Predicting Functional Roles of Non-Coding DNA
Built a multi-omics deep neural network that classifies regulatory elements in the non-coding 98 percent of the human genome as promoters or enhancers, then used SHAP explainable AI to open the black box, prioritizing 1,088 computationally identified enhancer candidates.
Endothelial ATAC-Seq in Cardiovascular and Neurodegenerative Disease
Applied ATAC-Seq to profile chromatin accessibility in endothelial cells, examining the regulatory changes that connect cardiovascular and neurodegenerative disease.
Classifying Primary Progressive Aphasia With Explainable AI
Developed multi-modal explainable AI models for classifying Primary Progressive Aphasia (PPA), making diagnostic machine learning interpretable for clinicians.
Compiling WCA Megaminx Scrambles for a Two-Axis Machine
Developed a system for compiling official WCA Megaminx scrambles for a two-axis, four-primitive machine, bridging competitive cubing with computational algorithms.
AI-Driven EEG Depression Detection
Developed an AI-driven framework for detecting depression using EEG signal analysis, enabling non-invasive mental health screening.
Blood Pressure Recovery via Wrist PPG Simulation
Developed a differentiable forward simulation framework for recovering blood pressure measurements from wrist PPG waveforms, enabling non-invasive cardiovascular monitoring.