Minmin Chen

Minmin Chen

About Me

I am a principal research scientist at Google Deepmind, leading efforts on building conversational AI systems through RL and personalization. I received my PhD from Washington University in St. Louis, advised by Kilian Weinberger. My main research interests are in reinforcement learning and bandits algorithms and their applications to recommendation and assistive systems. I recently received the best paper award from WSDM 2024 for our work on Exploration. I serve as guest editor for Journal of Machine Learning, and Area chairs for Neurips, ICML, ICLR and RecSys.

Email me at minminc@google.com or contact me at LinkedIn.

Talks and Activities
  • [2024 Jul] Keynote at 2024 International Conference on Theory of Information Retrieval on Exploration: Measurements and Systems.
  • [2024 May] Keynote at 2024 Web Conference 2ND WORKSHOP ON RECOMMENDATION WITH GENERATIVE MODELS on LLMs for Recommendations: A Hybrid Approach.
  • [2024 Apr] Co-organizing 2024 KDD workshop on Two-sided Marketplace Optimization: Search, Pricing, Matching & Growth
  • [2024 Mar] Our paper on Long Term Value of Exploration: Measurements, Findings and Algorithms just won the Best Paper Award at WSDM 2024.
  • [2023 Dec] Co-organizing 2024 AAAI workshop on Synergy of Reinforcement Learning and Large Language Models (RL+LLMs).
  • [2023 Sep] Invited talk at 2023 RecSys LARGE-SCALE VIDEO RECOMMENDER SYSTEMS on Intents and Journeys: An LLM approach.
  • [2023 Sep] Invited talk at 2023 RecSys workshop on CONSEQUENCE: Causality, Counterfactuals & Sequential Decision-Making on Exploration.
  • [2023 Aug] Invited talk at 2023 AI Boot Camp (NTU, Aug. 17) on ALLY: Large Language Models for Recommendations.
  • [2023 Jun] Invited talk at 2023 Netflix Personalization, Recommendation and Search on ALLY: Large Language Models for Companion Recommenders.
  • [2023 May] Guest lecture at Stanford class on Human Centered Artificial Intelligence on Recommender Systems: Reinforcement Learning, Exploration and Languages.
  • [2023 Apr] Keynote at 2023 WebConf workshop on Decision Making for IR and RecSys on Exploration in Recommender Systems: Measurements and Algorithms.
  • [2022 Dec] Co-organizing 2022 Neurips workshop on RL for Real Life.
  • [2022 Nov] Guest lecture at Stanford class on Advance Survey of Reinforcement Learning on Surrogate for Long Term User Experiences in RecSys.
  • [2022 Feb] Invited talk at 2022 WSDM Industry Day on Measuring Exploration in Recommender Systems.
  • [2021 Dec] Invited talk at 2021 Neurips workshop on Offline Reinforcement Learning on Batch Reinforcement Learning for Recommender Systems.
  • [2021 Nov] Co-organizing 2022 Google workshop on Long-term Dynamics for Responsible Recommendation Systems.
  • [2021 Sep] Invited talk at 2021 RecSys Industry Day Talk on Exploration in Recommender Systems.
  • [2021 Jul] Co-organizing 2021 ICML workshop on RL for Real Life, moderating the RL for RecSys panel.
  • [2021 Jul] Co-organizing 2021 Google Research Reinforcement Learning workshop.
  • [2021 Jul] Keynote at 2021 SIGIR symposium on IR in practice (SIRIP) with Ed Chi on Beyond Being Accurate: Solving Real-World Recommendation Problems.
  • [2020 Oct] Invited talk at 2020 Search Engines Amsterdam on New Advances in Reinforcement Learning for Recommender Systems.
  • [2020 Sep] Invited talk at 2020 RecSys workshop on Bandit and Reinforcement Learning from User Interactions on New Applications of Bandits and Reinforcement Learning for Recommender Systems.
  • [2019 Aug] Co-organizing 2019 KDD workshop on Deep Reinforcement Learning for Knowledge Discovery.
  • [2019 Aug] Co-organizing 2019 KDD workshop on Offline and Online Evaluation of Interactive Systems.
  • [2019 May] Invited talk at 2019 Netflix workshop on Personalization, Recommendation and Search on Reinforcement Learning for Recommender Systems.
  • [2019 Feb] Invited talk at 2019 WSDM Industry Day, won best Industry Day presentation award.
  • [2018 Oct] Invited talk at 2018 RecSys workshop on Offline Evaluation for Recommender Systems (REVEAL) on RL for RecSys: A Case Study on YouTube.
  • Area chair for Neurips(2019-2021, 2023), ICLR(2019-2024), ICML (2019-2023), AISTATS 2019, RecSys 2024.
  • Select Publications (Google Scholar)

    Machine Learning and AI

    Recommendation Systems