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
Suriya D.Eye-Tracking Signatures for Early Detection of Alzheimer's Disease
Ashwajit W.First-author simulation research, oral presentation at BICA 2026
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 IEEE ICPCSN 2026
Srihaan E.Published at IEEE CIBCB 2026
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+ participants
A 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.
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.
Optimized Medical Drone Delivery in Wildfire Environments
Developed an optimized framework for medical drone delivery in wildfire environments, addressing route planning and emergency response logistics.
AI Framework for Predicting Functional Roles of Non-Coding DNA
Developed an AI framework to predict the functional roles of non-coding DNA sequences, applying deep learning to genomics and bioinformatics.
CBC-Based Machine Learning for Anemia Severity Screening
Developed a machine learning model using complete blood count (CBC) data to screen and classify anemia severity, enabling faster and more accessible diagnostics.
Detecting Elevated Blood Lactate Levels via PPG Waveforms
Developed a method to detect elevated blood lactate levels using single 30-second PPG waveforms, enabling non-invasive monitoring for clinical and athletic applications.