I am a machine learning and computer vision engineer at The Johns Hopkins Applied Physics Lab. I graduated from UC Davis with a Master's in computer science, and from UC Berkeley with a double major in computer science and data science.
My research interests and background include machine learning, graph understanding, static ensemble pruning, computer vision, large language models, and generative tiemseries models. I have previously worked at Nokia as a generative ML engineer, AWS as a software engineer, and the Berkeley AI Lab (BAIR) as a ML researcher. I have TA-ed for programming, probem solving, and computer architecture at UC Davis, was a TA for Foundations of Data Science at Berkeley, and am a member of the CS honor society Upsilon Pi Epsilon.
Note-taking assistant that transcribes and summarizes live audio
User-interactive maze with toggleable difficulty
Simulating metaballs via constructive gaussian blur
Interactive visualization for shortest path algorithms