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