Early career researcher with an interdisciplinary background in Biomedical and Electrical Engineering, having expertise in Physics-based Deep Learning, Foundation Models, and Generative Artificial Intelligence workflows. Research experience includes designing hybrid neural network frameworks to connect physics principles with deep learning approaches for solving non-linear inverse problems, thus enabling reconstruction of high-quality biomedical signals. Technical experience involves computational optics, medical imaging processing, embedding, and clinical infrastructure evaluation.