I work on video reasoning and the evaluation of vision-language models. I build benchmarks and run large-scale experiments to measure how these models reason about the visual world—and where they fail.
I'm also interested in Physical AI, world models, and making AI more trustworthy and interpretable. I'm part of VBVR-Pro, VBVR, and Grow AI.
Selected Publications
* equal contribution · † equal advising · ✉ corresponding author · ✓ accepted
A Very Big Video Reasoning Suite (VBVR)
ICML 2026🤗 Hugging Face #1 Paper of the Month · Feb 2026
arXiv· Website· EvalKit· Data· Benchmark· Leaderboard· Model
Vision Language Models Cannot Reason About Physical Transformation (ConservationBench)
ICML 2026Egocentric Bias in Vision-Language Models (FlipSet)
CogSci 2026🏆 Sayan Gul Award · CogSci 2026
(Best Undergraduate Student Paper)
Assessing Perceptual Metacognition in Vision-Language Models
CogSci 2026AGI as Second Being: The Structural-Generative Ontology of Intelligence
Preprint“True intelligence exists only when a system can generate new structures, coordinate them into reasons, and sustain its identity over time.”