| Apr 30, 2026 | Our paper Benchmarking World-Model Learning via Environment-Level Queries was accepted at ICML 2026. The paper introduces WorldTest, a protocol for evaluating world-model learning through environment-level queries that go beyond next-frame prediction — testing whether agents can predict unobserved states, plan action sequences, and detect changes in dynamics. We instantiate WorldTest with AutumnBench, a suite of 43 interactive grid-world environments and 129 tasks across three families: masked-frame prediction, planning, and predicting changes to causal dynamics. I’ll be presenting the poster at the conference. |
| Apr 03, 2026 | Excited to share that I’ll be joining the ELLIS PhD Program as an incoming PhD student at TU Darmstadt, advised by Angela Yu in the Computational Modelling of Intelligent Systems lab. |
| Jul 18, 2025 | Presented a poster at ICML 2025 in Vancouver, Canada, as part of Basis on AutumnBench at the World Model Learning Workshop. |
| Aug 05, 2024 | Started as Research Trainee at Basis, New York, advised by Zenna Tavares. I’m contributing to Project MARA (Modeling, Abstraction, and Reasoning Agents), which aims to build AI systems capable of everyday scientific discovery through active experimentation and abstract reasoning. |