Parnian Kassraie

I am a 4th year doctoral student in Computer Science at ETH Zurich, fortunate to be advised by Andreas Krause and Peter Bühlmann. My Ph.D. is generously supported by a Google PhD Fellowship. I am interested in statistics, optimization, and machine learning, often in the context of reinforcement learning and sequential decision-making.

I spend the Spring semester 2025 at Carnegie Mellon University as a research scholar advised by Aaditya Ramdas. This appointment was supported by the ETH Zurich Doc.Mobility Fellowship. In 2024, I was a student researcher at Google DeepMind where I worked on fundamentals of RL for LLM alignment hosted by Olivier Bachem. Prior to that, I interned at Apple MLR with Marco Cuturi, developing a solver for the Optimal Transport problem.

I completed my M.Sc. at ETH, under the supervision of Andreas Krause and Fanny Yang, with a thesis on Contextual Neural Bandits. Before coming to ETH, I did a dual B.Sc. in Electrical Engineering and Computer Science at Sharif University of Technology. My thesis was on Visualizing Adversarial Attacks on Convolutional Neural Networks, which I wrote with Nassir Navab and Federico Tombari at TU Munich.

News

• [Jul-25] Passed my Ph.D. exam with Kevin Jamieson and Aldo Pacchiano kindly serving as the committee.
• [Jun-25] Organizing the Two Faces of Optimization workshop at ETH Zurich.
• [Apr-25] Organizing the EXAIT workshop at ICML 2025.
• [Oct-24] Received a G-Research PhD Prize in Mathematics.
• [Sep-24] Was awarded a Google Ph.D. Fellowship in Machine Intelligence. [ETH media]
• [Aug-24] Finished my internship at Apple MLR (Paris) with a short talk on my project, Progressive Entropic OT.
• [Mar-24] Was awarded the ETH Doc.Mobility Fellowship, for a research visit with Aaditya Ramdas.
• [Nov-23] Instance-Dependent Generalization Bounds via OT to appear in JMLR.
• [Jun-23] Serving as the head teaching assistant for Probabilistic Artificial Intelligence.
• [Jun-21] Started a PhD.