Ningren (Peter) Han
EECS PhD @ MIT
About Me
Hi, I'm Peter. I'm currently an AI Researcher at Google DeepMind, where I work on Gemini post-training and agentic research with the core Gemini team under Heng and Quoc. Prior to joining DeepMind, I was a Senior Staff Software Engineer and Manager at YouTube, leading a flagship recommendations team of 35+ full-time machine learning engineers. I earned my PhD in EECS from MIT, where I applied computational and statistical methods to problems in optical spectroscopy.
I am passionate about both applied and foundational machine learning research, and have been fortunate to work on a wide range of impactful projects throughout my career. At YouTube, I developed deep expertise in large-scale recommendation systems and LLM-powered applications for real-world products. More recently, I have shifted toward foundational research in core LLM development at Google DeepMind. My work has been recognized at top venues including RecSys, WWW, KDD, and ACL. Earlier in my career, I also contributed to research published in leading scientific journals such as Nature Photonics and Nature Communications. I remain excited about revisiting some of these early-career research topics through the lens of LLMs and autonomous agents.
Selected Recent Publications
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Vectorizing the trie: Efficient constrained decoding for LLM-based generative retrieval on accelerators.
Zhengyang Su, Isay Katsman, Yueqi Wang, Ruining He, Lukasz Heldt, Raghunandan Keshavan, Shao-Chuan Wang, Xinyang Yi, Mingyan Gao, Onkar Dalal, Lichan Hong, Ed Chi, Ningren Han.
arXiv preprint arXiv:2602.22647, 2026.
Read paper | GitHub -
PLUM: Adapting pre-trained language models for industrial-scale generative recommendations.
Ruining He, Lukasz Heldt, Lichan Hong, Raghunandan Keshavan, Shifan Mao, Nikhil Mehta, Zhengyang Su, Alicia Tsai, Yueqi Wang, Shao-Chuan Wang, Xinyang Yi, Lexi Baugher, Baykal Cakici, Ed Chi, Cristos Goodrow, Ningren Han, He Ma, Romer Rosales, Abby Van Soest, Devansh Tandon, Su-Lin Wu, Weilong Yang, Yilin Zheng.
Accepted to ACM Web Conference (WWW) 2026; arXiv preprint arXiv:2510.07784.
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LLM-powered nuanced video attribute annotation for enhanced recommendations.
Boyuan Long, Yueqi Wang, Hiloni Mehta, Mick Zomnir, Omkar Pathak, Changping Meng, Ruolin Jia, Yajun Peng, Dapeng Hong, Xia Wu, Mingyan Gao, Onkar Dalal, Ningren Han.
Proceedings of the Nineteenth ACM Conference on Recommender Systems, New York, NY, USA, 2025, pp. 1002–1005.
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Balancing fine-tuning and RAG: A hybrid strategy for dynamic LLM recommendation updates.
Changping Meng, Hongyi Ling, Jianling Wang, Yifan Liu, Shuzhou Zhang, Dapeng Hong, Mingyan Gao, Onkar Dalal, Ed Chi, Lichan Hong, Haokai Lu, Ningren Han.
Proceedings of the Nineteenth ACM Conference on Recommender Systems, New York, NY, USA, 2025, pp. 919–922.
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User feedback alignment for LLM-powered exploration in large-scale recommendation systems.
Jianling Wang, Yifan Liu, Yinghao Sun, Xuejian Ma, Yueqi Wang, He Ma, Zhengyang Su, Minmin Chen, Mingyan Gao, Onkar Dalal, Ed H. Chi, Lichan Hong, Ningren Han, Haokai Lu.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track), Vienna, Austria, 2025, pp. 996–1003.
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Reducing symbiosis bias through better A/B tests of recommendation algorithms.
Jennifer Brennan, Yahu Cong, Yiwei Yu, Lina Lin, Yajun Peng, Changping Meng, Ningren Han, Jean Pouget-Abadie, David M. Holtz.
Proceedings of the ACM Web Conference 2025 (WWW '25), Sydney, Australia, 2025, pp. 3702–3715.
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Country-diverted experiments for mitigation of network effects.
Lina Lin, Changping Meng, Jennifer Brennan, Jean Pouget-Abadie, Ningren Han, Shuchao Bi, Yajun Peng.
Proceedings of the 18th ACM Conference on Recommender Systems, Bari, Italy, 2024, pp. 765–767.
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LLMs for user interest exploration in large-scale recommendation systems.
Jianling Wang, Haokai Lu, Yifan Liu, He Ma, Yueqi Wang, Yang Gu, Shuzhou Zhang, Ningren Han, Shuchao Bi, Lexi Baugher, Ed H. Chi, Minmin Chen.
Proceedings of the 18th ACM Conference on Recommender Systems, Bari, Italy, 2024, pp. 872–877.
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For a complete list of publications and patents, including earlier academic work, please see my Google Scholar profile.
Education
Massachusetts Institute of Technology 2011 – 2018
TA for Graduate Machine Learning and Deep Learning Courses (one of the top-rated TAs).
Awarded Siebel Scholar (1 out of 5 in the department).
National University of Singapore 2007 – 2011
Received top university awards including the Lee Kuan Yew Gold Medal, Institute of Engineers Singapore Gold Medal, Outstanding Undergraduate Researcher Prize, Dean's List, Full Undergraduate Scholarship, and more.
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