I am a third-year Ph.D. student in Information Systems at the University of Maryland, Baltimore County (UMBC), specializing in Artificial Intelligence and Machine Learning. I am a Graduate Research Assistant in the Mobile Pervasive and Sensor Computing (MPSC) Lab, advised by Prof. Nirmalya Roy, and a Graduate Teaching Assistant with Prof. Zhiyuan Chen. I am also affiliated with the Center for Research in Use-Inspired Cyber-Physical Systems (CYPRESS).

My research focuses on trustworthy multimodal AI for healthcare. I develop methods for contactless physiological monitoring, estimating breathing and other vital signs from ordinary video and multimodal sensor data, using computer vision, time-series modeling, and vision-language models. A central question in my work is how AI systems use physiological evidence: I study where vision-language models and LLM-based agents fail, and make their outputs more reliable through calibration, evidence-grounded reasoning, uncertainty-aware inference, and counterfactual auditing, with particular attention to separating failures of perception, insufficient evidence, and reasoning.

I also care about getting these systems out of the lab. My work extends to efficient on-device inference on edge hardware and mobile robots, including field experiments with the DEVCOM Army Research Laboratory and demonstrations on the NSF-supported testbeds at CYPRESS, UMBC.

Previously, I was a research assistant at the Advanced Medical Engineering Research Institute (AMERI), University of Hyogo, Japan, as a HUMAP Fellow, working with Prof. Syoji Kobashi and Prof. Md Belayat Hossain on medical image processing and surgical video understanding. I have also worked as a Graduate Research Assistant in the QUEST Lab at the University of North Carolina at Charlotte, and spent two years as a Lecturer in Computer Science and Engineering at Leading University, Bangladesh.