Scholar

Abhinav Gupta

Google Scholar ID: jAaCd7YAAAAJ

Research Scientist, Google DeepMind

Reinforcement LearningNatural Language ProcessingMachine LearningArtificial Intelligence

Citations & Impact

All-time

Citations

870

H-index

i10-index

Publications

Co-authors

Contact

Publications

1 items

2026

Cited

Resume

Academic Achievements

- Thesis: 'Self-play for human-agent communication'
- Paper: 'Dynamic population-based meta-learning for multi-agent communication with natural language', NeurIPS 2021
- Paper: 'On the interaction between supervision and self-play in emergent communication', ICLR 2020
- Paper: 'Capacity, Bandwidth, and Compositionality in Emergent Language Learning', AAMAS 202

Research Experience

- Google DeepMind, London, advised by Grzegorz Swirszcz, Wojciech Czarnecki, and Oriol Vinyals, working on opponent behavior modeling
- Meta AI, Seattle, advised by Madian Khabsa and Roberta Raileanu, improving generalization in RL using uncertainty estimates
- Microsoft Research NYC, advised by Jordan Ash, replacing PPO with weighted SFT in RLHF
- Google Research Labs team, Mountain View, advised by Navneet Potti, enhancing code correctness in LLMs through RL with execution feedback
- Microsoft Research Cambridge, working with Raluca Georgescu, Sam Devlin, and Katja Hofmann, learning human-like behavior using offline RL and imitation learning

Education

Ph.D. from the Department of Computer Science and Operations Research at the University of Montreal, advised by Christopher Pal; Master's degree from the Courant Institute of Mathematical Sciences at New York University.

Background

Research interests include the effects of self-play in emergent languages arising in multi-agent communication systems, with a focus on computer science and operations research.

Miscellany