Courses

University of California Berkeley

• Statistical Learning Theory (Fall 2020)

• Computer Vision (Spring 2020)

• Theoretical Statistics (Fall 2019)

• Convex Optimization and Approximation (Spring 2019)

• Principles of Magnetic Resonance Imaging (Spring 2019)

• Topics in Machine-learning, Inverse-problems, and Data Analysis in Computational Neuro and Medical Imaging (Fall 2018)

• Advanced Topics in Electrical Engineering: Advanced Topics in Signal Processing (Fall 2018)

• Deep Reinforcement Learning (Fall 2018)