Frontotemporal dementia, a specific type of dementia, is extremely hard for doctors to diagnose. A highly accurate model means little if doctors cannot interpret or trust its decisions. Under the guidance of Dr. Shihab Shamma and Maryam Shaghaghi at UMD, I built a system that explains its decisions in plain terms, showing which brain patterns matter and why, to help doctors make more better & more confident diagnoses.

For this research, I was recognized by Regeneron Pharmaceuticals as a STS Top 300 Scholar.

I analyzed brain activity patterns from different regions and frequencies. The challenge was figuring out which patterns actually help with diagnosis versus which ones just add confusion. By testing each pattern individually, I identified the most reliable indicators that doctors can trust and understand.