CV
Education
Machine Learning Research Intern
University of Washington · Seattle, WA
High School Student
Tesla STEM High School · Redmond, WA
Experience
Lead Researcher
University of Washington & Independent Research
Biomedical Machine Learning Researcher
IEEE BIBM ML4BMI Workshop & SPIE Medical Imaging 2027
Autonomous Software Lead
FIRST Tech Challenge (FTC Team 23511)
Web Developer
Competitive Programming Initiative (CPI)
Student Ambassador
USA International AI Olympiad (USAIIAO)
Certified Referee
Sno-King Ice Hockey Association · Pacific Northwest
Honors and Awards
FIRST Tech Challenge (FTC)
4th in World Championship Division · 2nd Place World Inspire Award
USA Computing Olympiad (USACO)
Gold Division Qualifier
Washington State Science & Engineering Fair (WSSEF)
1st Place · High School Research & Engineering
Technology Student Association (TSA)
National Conference Semifinalist
Selected Publications & Preprints
CalAD: A Calibrated MRI Baseline for Alzheimer’s Detection on OASIS-3 (Expanded Version)
Andrew Ma, Khush Mehta · Accepted as Poster at SPIE Medical Imaging 2027
CONFLUENCE: Does Cross-Scale Graph Attention Help Watershed Vegetation Forecasting?
Andrew Ma · 9th ACM SIGSPATIAL International Workshop on AI for Geographic Information Systems (ACM GeoAI 2026 Agenda)
Beyond Site Decodability: When Does a Scanner Shortcut Actually Inflate Diagnostic Performance?
Andrew Ma · Machine Learning for Health (ML4H 2026 Findings Track / OpenReview)
CalAD: A Calibrated MRI Baseline for Alzheimer’s Detection on OASIS-3
Andrew Ma · IEEE BIBM 2026 — Machine Learning for Biomedical Informatics (ML4BMI) Workshop
Attention-Augmented Temporal Fusion Transformer for Short-Horizon Hypoglycemia Prediction in Type 1 Diabetes
Andrew Ma, Srihith Chennareddy · Endocrine Practice / AACE 2026 (Preprint on Research Square)
CropViT: Climate-Aware Vision Transformer Model for Crop Yield Prediction
Srihith Chennareddy, Andrew Ma, Yen-Chu Weng · 2026 7th International Conference on Machine Learning and Human-Computer Interaction (MLHMI 2026 / IEEE Xplore, Accepted Feb 8, 2026; Oral Presentation at JpGU-AGU 2026)
Spatial Deep Learning for Environmental DNA (eDNA) Localization and Biodiversity Mapping
Andrew Ma, Pedro Brandão Dias Ferreira Pinto · Preprint / Under review (In collaboration with University of Washington)
PSTL: Investigating Particle Scattering in Triply Periodic Minimal Surface Lattices
Andrew Ma, Srihith Chennareddy, C. Stoney, S. Brown, M. Chennareddy, A. Singh · Spring 2026 APS Northwest Section Meeting (APS PNW), Accepted May 21, 2026
Quantifying Non-Gaussian Scattering Tails in Micro-Heterogeneous Phantoms for Proton Therapy Applications
Srihith Chennareddy, Andrew Ma, C. Stoney, S. Brown, A. Singh · Spring 2026 APS Northwest Section Meeting (APS PNW), Accepted May 21, 2026
Technical Skills
Vision Transformers (ViTs), Graph Neural Networks (GNNs), Temporal Attention, Token Sparsification, Context Compression, Uncertainty Calibration, PyTorch
Remote Sensing, Satellite Multispectral Imagery, Climate Modeling, Brain MRI Analysis, Environmental DNA (eDNA) Spatial Mapping
Python, C++, Java, Git, Linux, Motion Profiling & Trajectory Optimization (Pedro Pathing), High-Performance Computing (HPC)