Courses taken (S = Stanford, M = Michigan)
Machine Learning / Statistics
- (S) CS 229 Machine Learning
- (S) CS 221 Artificial Intelligence
- (S) CS 230 Deep Learning
- (S) CS 20 Tensorflow for Deep Learning Research
Computer Science
- (S) CS 106B Programming Abstractions
- (S) CS 107 Computer Organization & Systems
- (S) CS 42 Contemporary Javascript
Numerical Methods / Mathematics
- (S) EE 263 Linear Dynamical Systems
- (S) EE 261 Fourier Transform & Applications
- (M) PHYSICS 211 Computational Physics
Photonics
- (S) EE 234 Photonics Laboratory
- (S) EE 236B Guided Waves
- (M) EE 336 Nanophotonics
Nonlinear Dynamics / Complexity
- (M) PHYS 413 Nonlinear Dynamics & Chaos
- (S) CMPLXSYS 511 Theory of Complex Systems
- (M) CMPLXSYS 535 Theory of Social and Technological Networks
Physics
- Quantum Mechanics (through quantum field theory I)
- Electricity and Magnetism (through graduate level)
- Classical Mechanics (through graduate level)
- Statistical Mechanics (through graduate level)
- (S) PHYS 211 Continuum Mechanics