Scholar
Natasha Jaques
Google Scholar ID: 8iCb2TwAAAAJ
University of Washington, Google Research
Social reinforcement learning
Machine learning
deep learning
multi-agent
human-AI interaction
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Citations & Impact
All-time
Citations
5,929
H-index
29
i10-index
40
Publications
20
Co-authors
16
list available
Contact
Email
natashamjaques@gmail.com
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Publications
40 items
Reflections and Fragments: Securing LLMs Against Sequential Mosaic Attacks
2026
Cited
0
Mitigating Social Sycophancy via Pluralistic Preference Optimization
2026
Cited
0
From Solo to Social Learning: Characterizing Recursive Social Improvement in LLMs
2026
Cited
0
Forty Shades of Blue: Quality-Diversity Alignment via Mode-Conditioned Reinforcement Learning
2026
Cited
0
Tapes Together Strong: The Co-evolution of Computation and Cooperation
2026
Cited
0
Demystifying Reinforcement Learning Post-Training of Language Models
2026
Cited
0
SPADE: Self-Play in Adaptive Synthetic Executable Environments
2026
Cited
0
Debate Training Reduces Reward Hacking in RLAIF
2026
Cited
0
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Resume
Academic Achievements
2023 Best Paper, AAAI Workshop on Representation Learning for Responsible Human-Centric AI
2021 Outstanding PhD Dissertation Award, Association for the Advancement of Affective Computing
2021 Best of Collection, IEEE Transactions on Affective Computing (impact factor: 10.5)
2020 Best Paper, NeurIPS Workshop on Cooperative AI
2019 Honorable Mention for Best Paper, ICML
2019 Rising Stars in EECS Pitch Competition Winner
2019 Best Paper Nominee, NeurIPS Workshop on Conversational AI
2017 Centennial Alumni of Distinction, Campion College
2016 Best Paper, NeurIPS Workshop on ML for Healthcare
2016 Best Demo, NeurIPS
Work featured in Science, MIT Technology Review, IEEE Spectrum, Quartz, National Geographic, Boston Magazine, CBC radio, and more
Research Experience
During PhD at MIT, developed RL-based language model fine-tuning and human feedback learning techniques later built upon by OpenAI’s RLHF work
Developed methods for improving multi-agent coordination through optimization of social influence
Interned at DeepMind and Google Brain; served as OpenAI Scholars Mentor
Visiting Postdoctoral Scholar in Sergey Levine’s group at UC Berkeley
As Senior Research Scientist at Google Brain, built adversarial environment generation methods to enhance RL agent robustness
Co-authors
11 total
Asma Ghandeharioun
Sr. Research Scientist, Google DeepMind
Douglas Eck
Google Research, Brain Team
Shixiang Shane Gu
Google DeepMind
Lynn H. Kaack
Hertie School
David Rolnick
McGill University, Mila Quebec AI Institute
Richard E Turner
Professor, University of Cambridge
Cristina Conati
Professor of Computer Science, University of British Columbia
José Miguel Hernández-Lobato
Professor of Machine Learning, University of Cambridge