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Resume (English only)
Academic Achievements
Published multiple papers including 'Explaining Decisions with a Corpus of Examples' (NeurIPS, 2023), 'Simulating and Benchmarking Resource Allocation Policies' (NeurIPS, 2023), 'Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments' (ICML, 2023), etc.
Research Experience
A Research Scientist at Google DeepMind, working in the Gemini pre-training team. Interned at Google DeepMind in the Deep Reinforcement Learning team, studying representation and exploration, and worked in the Game Theory team on language model training and alignment.
Education
Ph.D. in Mathematics from the University of Cambridge, advised by Mihaela van der Schaar; M.S. in Computer Science from the University of Oxford; B.A. in Economics (Finance) from Princeton University.
Background
Research interests include generative modeling, reinforcement learning, and causal inference, focused on modeling, understanding, and improving decision-making over time. Previous life: investment banking, economic research, and software engineering.