Jiang Bian, Ph.D.

Senior Principal Researcher and Research Manager, Microsoft Research Asia

Director of MSR Asia Industry Innovation Center

Work Email: jiang.bian@microsoft.com

Personal Email: jiang.bian.prc@gmail.com


I am a Principal Researcher and Research Manager at Microsoft Research. And, I am currently playing the Director of MSR Asia Industry Innovation Center (MIIC). I am leading this center with the mission of building up innovative and disruptive technologies as well as forward-looking insights to drive the digital transformation for important industries. We have been focusing on designing cutting-edge machine learning algorithms into real-world application scenarios, including finance, supply-chain, healthcare and sustainability.

Prior to that, I was a Senior Scientist in Yidian Inc., a startup company in China, where I have been working on recommendation and search problems. I also used to work at Yahoo! Labs and did a lot of studies on content optimization and personalization for Yahoo!'s key content modules as well as local content search and recommendation for Yahoo!'s local services.

I received my B.S. from Peking University (2006) and Ph.D. from Georgia Institute of Technology (2010), both in Computer Science. My dissertation was on information retrieval, data mining, and machine learning techniques on general Web search and social media search, advised by Prof. Hongyuan Zha.

I authored tens of academic research papers receiving hundreds of citations, filed a couple of U.S. patents, and served as PC member/Peer reviewer for a few international conferences and journals.


  • [Jan 2023] Our paper "Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping" has been accepted by ICLR 2023.

  • [Jan 2023] Our paper "Learning Physics-Informed Neural Networks without Stacked Back-propagation" has been accepted by AISTATS 2023.

  • [Jan 2023] Our paper "Curriculum Offline Reinforcement Learning" has been accepted by AAMAS 2023.

  • [Nov 2022] Our paper "Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem" has been accepted by AAAI 2023.

  • [Nov 2022] Our paper "H-TSP: Hierarchically Solving the Large-Scale Travelling Salesman Problem" has been accepted by AAAI 2023.

  • [Nov 2022] Our paper "TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets" has been selected as the ICDM2022 Best Student Paper Award runner-up.

  • [Oct 2022] Our paper "A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring" has been accepted by IEEE BIBM 2022.

  • [Oct 2022] Our paper "A Graph-based Spatiotemporal Model for Energy Markets" has been accepted by CIKM2022

  • [Sep 2022] Our paper "Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations" has been accepted by NeurIPS2022

  • [Aug 2022] Our paper "KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings" has been accepted by COLING 2022

  • [May 2022] Our paper "Learning Differential Operators for Interpretable Time Series Modeling" has been accepted by KDD2022.

  • [Apr 2022] Our paper "Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble" has been accepted by IJCAI-ECAI 2022.