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Distinguished Professor
School of Mathematical Sciences
Shanghai Jiao Tong University
800 Dongchuan Road
Minhang, Shanghai

E-mail: weidongl@sjtu.edu.cn

• 2011-- Professor, School of Mathematical Sciences and Institute of Natural Sciences, Shanghai Jiao Tong University
• 2009--2011 Postdoctoral Fellow, Department of Statistics, The Wharton School,University of Pennsylvania
• 2008--2009 Postdoctoral Fellow, Department of Mathematics, Hong Kong University of Science and Technology
• 2003--2008 Ph.D. in Mathematics, Zhejiang University, P.R. China

Honors and Awards

• National Excellent Doctoral Dissertation Award from China, 2010
• New World Mathematics Awards, Silver Award for the Ph.D Thesis, 2010.

Current Research Interests

• Modern statistics
• Probability
• Optimization

Recent Research

• A New Accelerated Off-Policy Stochastic Preconditioned TD(0) Algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence, to appear. 2025.
• Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning. Annals of Statistics, to appear. 2025
• Communication-Efficient Distributed Sparse Learning with Oracle Property and Geometric Convergence. Journal of the American Statistical Association, to appear. 2025
• ST_k: A Scalable Module for Solving Top-k problems. NeurIPS 2024.
• Majority Vote for Distributed Differentially Private Sign Selection. Annals of Statistics, to appear 2024. https://arxiv.org/abs/2209.04419[pdf]
• Distributed Estimation and Inference for Semi-parametric Binary Response Models. Annals of Statistics, to appear. 2024
• Distributed Estimation on Semi-Supervised Generalized Linear Model. Journal of Machine Learning Research, to appear. 2024
• Multi-consensus decentralized primal-dual fixed point algorithm for distributed learning. Machine Learning, 2024.[pdf]
• Robust Personalized Federated Learning with Sparse Penalization. Journal of the American Statistical Association, to appear. 2024
• Efficient Sparse Least Absolute Deviation Regression with Differential Privacy. IEEE Transactions on Information Forensics & Security, to appear. 2023
• Distributed Semi-Supervised Sparse Statistical Inference. IEEE Transactions on Information Theory, to appear. 2023
• Acceleration of stochastic gradient descent with momentum by averaging: finite-sample rates and asymptotic normality. Technical report, 2023.[pdf]
• Decentralized Reduced Rank Regression for Response Partition. Technical report, 2023.
• Fast Decentralized Median Value Estimation. Technical report, 2022.
• Accelerated online averaging over networks.Technical report, 2022.
• Fast and Robust Sparsity Learning over Networks: A Decentralized Surrogate Median Regression Approach. IEEE Transactions on Signal Processing, to appear. 2022.[pdf]
• Byzantine-Tolerant Distributed Multiclass Sparse Linear Discriminant Analysis, The 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022).
• DEMO: A Flexible Deartifacting Module for Compressed Sensing MRI, IEEE Journal of Selected Topics in Signal Processing, to appear. 2022.[pdf]
• Byzantine-robust distributed sparse learning for M-estimation. Machine Learning, to appear. 2021. [pdf]
• Variance reduced median-of means estimator for Byzantine-robust distributed inference. Journal of Machine Learning Research, 1-67. 2021.[pdf]
• First-order Newton-type estimator for distributed estimation and inference. Journal of the American Statistical Association, to appear. 2021.[pdf]
• Robust reduced rank regression in a distributed setting. Science China- Mathematics, to appear. 2021 [pdf]
• Distributed high-dimensional regression under a quantile loss function. Journal of Machine Learning Research, 182, 1-43. 2020[pdf]
• Bayesian decision process for budget-efficient crowdsourced clustering. International Joint Conferences on Artificial Intelligence, 2020.[pdf]
• Median matrix completion: from embarrassment to optimality. Proceedings of the 37 th International Conference on Machine Learning, Online, PMLR 119, 2020. [pdf]
• Distributed inference for linear support vector machine. Journal of Machine Learning Research, 20(113), 1-41. 2019 [pdf]
• Quantile regression under memory constraint. Annals of Statistics, 47 (6), 3244-3273. 2019 [pdf]

Former Phd students, Postdoc

• Tu Jiyuan, assistant professor, Shanghai University of Finance and Economics
• Wang Xiaozhou, assistant professor, East China Normal University
• Zhu Yunlong, assistant professor, Shanghai University
• Luo Shan (postdoc), associate professor, Shanghai Jiao Tong University

Master students

• 20+students in IT (Alibaba, Tencent, Ctrip,ByteDance, ...)