Teaching and supervision

Course coordination of the Seminar Course on Reinfocement Learning, University of Helsinki (Sep-Dec 2026)
This course is jointly coordinated with Petrus Mikkola. The main idea is to explore modern reinforcement learning through a journal-club format, with a focus on influential and recent research papers. Topics include model-free and model-based RL, offline and imitation learning, exploration, multi-agent RL, and reinforcement learning for language-model post-training.

Mini-tutorials on Monte Carlo methods, Cyber-Physical Systems group, Aalto University (Oct-Nov 2024)
All materials are available in this GitHub repository, which includes slides and Python code to reproduce the examples from these tutorials:

• Introduction to Monte Carlo and importance sampling (08/10/2024)
• Introduction to sequential Monte Carlo (05/11/2024 and 19/11/2024)

Guest lecturer, Aalto University (2024-2025)
Lectures in Stochastic Optimal Control in the course Digital and Optimal Control. Part of the Electrical Engineering and Automation master with major in Control, Robotics, and Autonomous Systems.

Teaching Assistant, Universidad Carlos III de Madrid (2017-2019)
112 hours conducting workshops in Linear Systems.

Teaching Assistant, Universidad Carlos III de Madrid (2017-2018)
5 hours conducting workshops in Linear Networks Analysis and Synthesis.

Co-supervision of ELLIS PhD student, University of Helsinki (2026-2030)
Vivian Phan will focus on Bayesian experimental design (BED) and preference ellicitation, being supervised as well by Prof. Arto Klami (UH) and Prof. Patrick Thiran (EPFL).

Co-supervision of PhD student, Aalto University (2025-2029)
Juri Voloskin will focus on Bayesian experimental design (BED) and control for prognostics in industrial applications (collaborating with ABB).

Co-supervision of B.Sc. thesis, Aalto University (Jan-Jun 2025)
Thesis title: Variational inference approaches to Bayesian optimal experimental design, Aditya Agrawal.