Recent

• Winter 2023/24. Non-parametric statistics course at Humboldt University of Berlin (at master level), co-lecturing with Vladimir Spokoinyi, in term 2023/24.

• August 2023. I taught a mini-course on the optimization perspective of gradient flow dynamics, introducing (beginner-friendly) concepts of gradient flows in the Eulidean and Wasserstein space, at the Workshop of Intelligent Autonomous Learning Systems 2023. Lecture slides available:
  • slides for the mini-course
  • slides for the introduction to our research
• July 2022, Ph.D. mini-couse on Data-Driven Modeling and Optimization of Dynamical Systems under Uncertainty, TU Berlin-Oxford IRTG Stochastic Analysis, TU Berlin, Berlin, Germany
  • Website
  • Coding exercises
    • Basics on ML and optimization
    • Chance-constrained and distributionally robust optimization
    • Numerical optimization for control
  • Whiteboard notes:
    • Day 1: Basics of statistical learning theory, continuous optimization whiteboard notes
    • Day 2: Mirror descent, stochastic approximation, distributionally robust optimization with Wasserstein distance and maximum mean discrepancy whiteboard notes
• August 2021, Leibniz MMS Summer School, Mini-course on Robust Optimization and Learning under Distribution Shift, Dagstuhl Castle, Saarland, Germany
  • Website
  • Slides
  • GitHub repository for slides and exercises

Older courses

(Construction WIP…)