Columbia EE · Yanai Tadashi Scholar · ML for neurotechnology
Decoding the brain into language.
I build machine-learning systems for brain–computer interfaces and biomedical imaging.
I'm an Electrical Engineering undergraduate at Columbia (B.S. 2028) and a Yanai Tadashi Scholar building machine-learning systems for brain–computer interfaces and biomedical imaging. My long-term aim is a portable device that decodes neural activity into language, so people who cannot speak can communicate. Outside the lab, I blow glass.
- Co-authored paper at ACM UIST 2026 on XR agent adaptation using BCI evidence
- 2 first-author abstracts at ISMRM 2026 on fast Ktrans mapping and accelerated CBV reconstruction
- Yanai Tadashi Scholar, supported on a full undergraduate merit scholarship (~7% selection rate)
- Only undergraduate in Columbia's Fall 2025 DSI Scholars cohort
- Only undergraduate finalists at the Millard Chan '99 Technology Challenge
- 2nd place at Columbia's Lion's Cage, five points from first on a 300-point rubric
- 6 research projects across 2 labs (selected work below)
- Mentors 2 high-school researchers at the Zuckerman Institute
- 3.90 GPA while carrying 21–24 credits per semester
Selected work
Multimodal Brain–Computer Interface
A foundation model that unifies EEG, ECoG, fMRI, and fNIRS in one shared representation, built in collaboration with Google DeepMind.
AI-PET: Pathology Maps from a Routine MRI
Deep models that synthesize amyloid-β and tau PET from non-invasive T1-weighted MRI, toward low-cost, large-scale Alzheimer's screening.
ResearcherX
An AI writing environment with a logic-validation engine that flags contradictions in AI-assisted drafts, with line-level provenance.
EchoID: Local, Identity-Aware Meeting Notes
A local-first meeting-notes pipeline that captures audio, recognizes recurring speakers with user-owned voiceprints, transcribes, summarizes, and exports Markdown.