Shushman Choudhury

Shushman Choudhury

I am an Artificial Intelligence researcher with expertise in foundation models, computational decision-making, and multi-agent systems. My work has been applied to diverse domains, including global-scale geospatial intelligence, autonomous mobility networks, and robotics.

At Google Research, I develop foundation models and applications for geospatial intelligence, human mobility, and the built environment. My contributions have driven interdisciplinary published research and real-world product impact across Google Maps, Ads, and other key platforms. Previously, as Research Lead at a Series A startup, I built intelligent digital platforms that optimized urban transportation and advanced smarter cities.

I hold a Ph.D. in Computer Science from Stanford, where my award-winning research on multi-agent decision-making for large-scale autonomous systems was covered by the BBC, Venture Beat, and IEEE Spectrum. I also earned an MS in Robotics from Carnegie Mellon, focusing on advanced robot planning techniques.

Recent News

Selected Publications

GEOS SIGSPATIAL 2025

Toward Foundation Models for Mobility Enriched Geospatially Embedded Objects
Siampou, M.D., Hsu, S.L., Choudhury, S., Arora, N. and Shahabi, C., (2025). SIGSPATIAL '25: Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems.
Spotlight talk in Vision Track
Paper

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Scalable Online Planning for Multi-Agent MDPs
Choudhury, S., Gupta, J. K., Morales, P., & Kochenderfer, M. J. (2022).
Journal of Artificial Intelligence Research, 73, 821-846.
Awarded Best Paper at AAMAS 2021.
Paper / Site

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Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints
Choudhury, S., Gupta, J. K., Kochenderfer, M. J., Sadigh, D., & Bohg, J. (2022). Autonomous Robots, 46(1), 231-247
Spotlight talk at Robotics: Science and Systems 2020.
Paper / Github / Video

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Efficient Large-Scale Multi-Drone Delivery using Transit Networks
Choudhury, S, Solovey, K., Kochenderfer, M. J., & Pavone, M. (2021).
Journal of Artificial Intelligence Research, 70, 757-788.
Selected Best Multi-Robot Systems Finalist at ICRA 2020.
Paper / Github / Video