Interested in working with me? I supervise strong and highly motivated students (primarily) from ETH on research and thesis projects in generative discovery via flow and diffusion models, covering theory, scalable generative methods, and applications in chemistry, biology, and physical sciences.

Student Research Supervision

ETH Zurich & Caltech — June 2023 – Present

I have had the opportunity to act as thesis or project advisor for several M.S. and B.S. students, including:

• Federico Arangath (2023, ETH, semester project, active exploration in MDPs)
• Noah Liniger (2023, ETH, semester project, active exploration in MDPs and generative bandits)
• Guy Schacht (2024, ETH, M.S. thesis, efficient preference learning on MDPs)
• Sven Gutjahr (2024, ETH, M.S. thesis, constrained flow generation)
• Cristian Perez Jensen (2025, ETH, M.S. thesis, reward-guided flow adaptation)
• Kimon Protopapas (2025, ETH, M.S. thesis, exploration via diffusion and flow models)
• Trevor Chen (2026, Caltech, semester project, discrete diffusion-based online molecular optimization)
• Ariel Dai (2026, Caltech, semester project, discrete diffusion-based online molecular optimization)
• Harini Vijayshankar (2025, ETH, M.S. thesis, flow-based protein structure exploration, ongoing)
• Benson Lee (2026, ETH, semester project, statistical theory of discovery, ongoing)
• Jan Kogler (2026, ETH, M.S. thesis, active flow expansion for material design, ongoing)
• Federico Nicolo’ (2026, EPFL/ETH, M.S. thesis, wet-lab driven flow expansion, ongoing)

Teaching Assistant

ETH Zurich — 2022 – Present

• Foundations of Reinforcement Learning (2022–2023) — homework preparation.
• Probabilistic Artificial Intelligence (2024–2025) — exam preparation; co-designed with Andreas Krause the new Diffusion Generative Models module (~500 students).
• Introduction to Machine Learning (2026) — exam preparation.

Mentoring

LeadTheFuture — November 2022 – Present

Mentor Italian students as they begin their academic and research journeys.