Dongsheng Li (李东胜)

Principal Research Manager
Microsoft Research Asia, Shanghai

dongshengli@fudan.edu.cn
ResearchGate
GoogleScholar


Dongsheng Li is currently a principal research manager with Microsoft Research Asia (MSRA), Shanghai, China, leading the MSRA Shanghai AI/ML Group. Meanwhile, he is an adjunct professor with School of Computer Science, Fudan University, Shanghai, China. Before joining MSRA Shanghai, he worked as a research staff member (RSM) with IBM Research - China, Shanghai, China. He obtained Ph.D. from School of Computer Science, Fudan University in 2012, and B.E. from Department of Computer Science and Technology, University of Science and Technology of China (USTC) in 2007. He is a senior member of ACM and IEEE, and has published two books on recommender systems and over 200 papers in prestigious journals (e.g., PNAS, Nature Communications and TPAMI) and conferences (e.g., ICML, NeurIPS and ICLR). His research interests focus on machine learning and its applications in brain science and healthcase. He has received several awards in recent years, including the 2018 IBM Corporate Award, the EACL 2024 Outstanding Paper Award, and the 2023 China Intelligent Computing Technology Innovators Award.

We are hiring researchers and interns. Please email me dongsli@microsoft.com if you are interested to join MSRA Shanghai.

Book: 李东胜,练建勋,张乐,任侃,卢暾,邬涛,谢幸  《推荐系统:前沿与实践》 电子工业出版社,2022

Book: Dongsheng Li, Jianxun Lian, Le Zhang, Tun Lu, Tao Wu, Xing Xie. Recommender Systems: Frontiers and Practices. Springer. 2024

Publication (by category)

Patents

  • Wind power predictability enhancement using hybrid energy storage system. Application no.: 201310501062.6. (in Chinese)
  • Wind power predictability enhancement by combining pitch control and ultracapacitor. Application no.: 201310500736.0. (in Chinese)
  • Work-piece defect inspection via optical images and ct images. US20170161884A1.
  • Job role identification. US20190279232A1.
  • Training a machine learning model in a distributed privacy-preserving environment. US20180336486A1.
  • Neural Network Training. US20180129917A1.
  • Privacy-Preserving Smart Metering. US20180060976A1.
  • Image orientation detection. US10121250B2.
  • Expense compliance checking based on trajectory detection. US20180137576A1.
  • Model based data processing. US20180068224A1.
  • Providing Computation Services with Privacy. US10333715B2.
  • Multi-dimensional root cause analysis based on cross-metrics. WO2023136871A1

Honour and Awards

  • Intel Fellowship, Intel, 2011
  • Excellent Graduate Student, Fudan University, 2012
  • Outstanding Technical Achievement Award, IBM Research, 2016
  • Outstanding Technical Achievement Award, IBM Research, 2017
  • Outstanding Technical Achievement Award, IBM Research, 2018
  • IBM Corperate Award, IBM, 2018
  • Outstanding Paper Award, EACL, 2024
  • 2023 China Intelligent Computing Technology Innovators Award, MIT Technology Review China & DeepTech, 2024