- Shape the future of agentic AI by pioneering new research directions in planning, reinforcement learning, multimodal reasoning, grounding, human-agent interaction, and alignment (e.g. reward modeling, automated task evaluation, AI safety).

- Advance the science hands-on through designing methods, building datasets, running experiments, and benchmarking against state of the art.

- Develop new methodologies that push the boundaries of AI agent capabilities and reliabilities, advancing both academic and product impacts, in collaboration with world-class scientists and engineers.

- Design and execute experiments end-to-end: from data collection and benchmarking, to model training and evaluation.

- Collaborate closely with engineers to integrate research prototypes into product.

- Publish and present results at top-tier conferences, contributing to the broader AI research community.

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