Relevant graduate-level coursework
- Computational Neuroscience: Circuits in the Brain (with Prof. Aurel A. Lazar)
- Brain-Computer Interfaces (with Prof. Paul Sajda)
- Neural Networks & Deep Learning (with Prof. Zoran Kostic)
- Foundations of Graphical Models (with Prof. David Blei)
- Machine Learning for Data Scientists (with Prof. John Paisley)
- Sparse Representation and High-dimensional Geometry (with Prof. John Wright)
- Statistical Learning for Biological and Information Systems (with Prof. Predrag R Jelenkovic)
- Statistical Signal Processing (with Prof. Don H. Johnson)
- Introduction to Random Processes and Applications (with Prof. Behnaam Aazhang)
- Convex Optimization (with Prof. Donald Goldfarb)
- Applied Math III: Dynamical Systems (with Prof. Marc W. Spiegelman)
- Bandits and Reinforcement Learning (with Prof. Alekh Agarwal and Prof. Alex Slivkins)
- Applied Functional Analysis (with Prof. Guillame Bal while he was at Columbia)