Yuantong Li (李沅桐) Senior Research Scientist Meta AI E-mail: liyuantong93 [@] gmail [DOT] com [Google Scholar] [Github] [LinkedIn] About me 2024 - Now, Senior Research Scientist at Meta. 2019 - 2024, Ph.D. in Statistics at UCLA.

Research interests

I’m an AI researcher and engineer focused on building large-scale intelligent systems at the intersection of recommendation systems, machine learning, and decision making. My work spans ranking and retrieval, cold-start recommendation, uncertainty estimation, and reinforcement learning for real-world platforms serving billions of interactions. I’m particularly interested in combining AI with causal inference, optimization, and statistical modeling to make machine learning systems more robust, adaptive, and trustworthy. Recently, I’ve been exploring how uncertainty-aware modeling and sequential decision frameworks can improve recommendation quality and long-term user value.

Outside of production ML systems, I enjoy thinking about market dynamics, complex systems, and the connection between statistical learning and real-world decision making.

Publications/Manuscripts

2026

• MBD: A Model-Based Debiasing Framework Across User, Content, and Model Dimensions
  Yuantong Li, Lei Yuan, Zhihao Zheng, Weimiao Wu, Songbin Liu, Jeong Min Lee, Ali Selman Aydin, Shaofeng Deng, Junbo Chen, Xinyi Zhang, Hongjing Xia, Sam Fieldman, Matthew Kosko, Wei Fu, Du Zhang, Peiyu Yang, Albert Jin Chung, Xianlei Qiu, Miao Yu, Zhongwei Teng, Hao Chen, Sunny Baek, Hui Tang, Yang Lv, Renze Wang, Qifan Wang, Zhan Li, Tiantian Xu, Peng Wu, Ji Liu.
  submitted.
  

• Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System
  Yuantong Li, Guang Cheng, and Xiaowu Dai.
  ICML 2026.
  

2024

• Epinet for Content Cold Start
  Hong Jun Jeon, Songbin Liu, Yuantong Li, Hunter Song, Ji Liu, Peng Wu, and Zheqing Zhu.
  submitted.
  

• Dynamic Matching Bandit For Two-Sided Online Markets
  Yuantong Li, Chi-hua Wang, Guang Cheng, and Will Wei Sun.
  submitted.
  

• Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints
  Yuantong Li, Guang Cheng, and Xiaowu Dai.
  ICML 2024.
  

2023

• Discussion of ‘‘Estimating Means of Bounded Random Variables by Betting’’ by Waudby-Smith and Ramdas
  Jiayi Li, Yuantong Li, and Xiaowu Dai.
  JRSSB 2023.
  

2022

• Graph Federated Learning with Hidden Representation Sharing
  Shuang Wu, Mingxuan Zhang, Yuantong Li, Carl Yang, and Pan Li.
  CIKM-FedGraph 2022.
  

• Residual Bootstrap Exploration for Stochastic Linear Bandit
  Shuang Wu, Chi-hua Wang, Yuantong Li, and Guang Cheng.
  UAI 2022.
  

• Debiasing Neural Retrieval via In-batch Balancing Regularization
  Yuantong Li, Xiaokai Wei, Zijian Wang, Shen Wang, Parminder Bhatia, Xiaofei Ma, and Andrew Arnold.
  NACCL Workshop 2022.
  

• Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning
  Pratik Ramprasad, Yuantong Li, Zhuoran Yang, Zhaoran Wang, Will Wei Sun, and Guang Cheng.
  JASA 2022.
  

2021

• Peel learning for pathway-related outcome prediction
  Yuantong Li, Fei Wang, Mengying Yang, Fan Yang, Edward Cantu, Hengyi Rao, and Rui Feng.
  Bioinformatics 2021.
  

• Online Forgetting Process for Linear Regression Models
  Yuantong Li, Chi-hua Wang, and Guang Cheng.
  AISTATS 2021.
  

2020

• A Non-Iterative Quantile Change Detection Method in Mixture Model with Heavy-Tailed Components
  Yuantong Li, Qi Ma, and Sujit K Ghosh.
  KDD 2020.
  

• Interactive Attention Networks for Semantic Text Matching
  Sendong Zhao, Yong Huang, Chang Su, Yuantong Li, and Fei Wang.
  ICDM 2020.