Resume
Computer science student at Stanford researching machine learning, computer vision, and spatial computing. pdf →
Experience
Computer vision for MRI imaging, advised by Dr. Olesya Melnichenko.
3D diffusion and long-context video understanding.
World models for zero-shot action understanding — a single model that predicts user actions from unlabeled video across 9 environments at 85.2% accuracy.
Drove development of CNN models generating realistic 3D hair reconstructions across demographics, boosting accuracy to 96% and enabling deployment on lightweight devices. Built a robust extraction pipeline with OpenCV and SAM segmentation, achieving clean segmentation on 98% of images.
Education
Relevant coursework: Data Structures & Algorithms, Operating Systems, Concurrency, Linear Algebra, Multivariable Calculus, Machine Learning, Computer Vision, Reinforcement Learning, Statistics, Combinatorics.
Activities & societies
- ·Stanford XR (Vice President)
- ·Stanford AI Club
- ·Stanford Neurotech
Programs
Selective program for students exploring quantitative trading and technology at Optiver.
Microsoft Research
Stanford AI Lab (SAIL)
Optiver FutureFocus