Graduate Coursework

  • -Advanced Optimization
  • -Advanced Probability I(Measure Theoretic)
  • -Advanced Probability II(Large Deviations, Gibbs Measures, Anticoncentration etc)
  • -Algorithmic Game Theory
  • -Applied Spatial Statistics
  • -Arithmetic Hyperbolic 3-Manifolds
  • -Asymptotic Statistics
  • -Combinatorial Optimization and Approximation Algorithms
  • -Decision Theory
  • -Individual Studies: Information Geometry + Differentiable Manifolds
  • -Mathematics of Deep Learning
  • -Modern Discrete Probability: From Random Graphs to Spin Systems
  • -Multivariate Statistics
  • -Randomised Algorithms
  • -Stability and Privacy in ML
  • -Statistical Learning Theory
  • -Theory of Distributed Systems

Teaching Assistant Roles

  • -Applied Machine Learning and Causal Inference
  • -Advanced Stochastic Processes (Graduate)
  • -Advanced Probability II (Large Deviations, Gibbs Measures, Anticoncentration etc) (Graduate)