Published in top machine learning conferences, contributing methods in compression and explainability that enable large-scale recognition and 3D reconstruction in real-world settings; notable works include SpeeDe3DGS, SplatSuRe, and TransFIRA.
Research Experience
Computer Vision Research Intern at Systems & Technology Research (STR), focusing on multimodal biometric recognition; Peer Research Mentor in the Capital One Machine Learning FIRE program at UMD, mentoring over 80 undergraduates in their first research experiences.
Education
Completed BS/MS in Computer Science at the University of Maryland (UMD) in 2024; currently a PhD student in Computer Science at UMD, advised by Professor Tom Goldstein.
Background
Research interests span deep learning, computer vision, and graphics, with a focus on 3D scene reconstruction, multimodal biometric recognition, and generative priors for robust vision systems. Aims to develop machine learning systems that are both efficient and trustworthy, advancing AI for real-world applications.