I'm a full-stack developer with a background in data science and statistics for quantum chemistry and computational biology, currently studying at UC Berkeley. I love building useful things at the intersection of web development, machine learning, and computational biology.

I’m enthusiastic about using machine learning and deep learning to solve meaningful problems in areas like computational biology and finance. Recent projects include toxicity prediction models in PyTorch and reinforcement learning for portfolio optimization and smarter decision making. I enjoy asking clear questions, running clean experiments, and shipping results.

I thrive in collaborative teams where sharing ideas sparks better solutions. When I’m not coding, I’m outdoors, diving into research, or tinkering with new tools to stretch my skills and learn something new every day.