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)