DongSheng Li (ζŽδΈœθƒœ)

Research Staff Member
IBM Research - China, Shanghai

Advisors: Ning Gu and Li Shang
ldsli@cn.ibm.com
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About

Dongsheng Li is currently a research staff member (RSM) with IBM Research - China, Shanghai, China. Meanwhile, he is an adjunct professor with School of Computer Science, Fudan University, Shanghai, China. Before joining IBM, he worked as postodoc researcher with the department of computer science and technology, Tongji University (supervised by Prof. Li Shang). He obtained Ph.D. from school of computer science, Fudan University in 2012 (supervised by Prof. Ning Gu), and B.E. from department of computer science and technology, University of Science and Technology of China (USTC) in 2007. He also visited University of Colorado Boulder as a visiting scholar from 2010.8 to 2011.2 (supervised by Prof. Qin Lv).

Dongsheng Li is member of CCF, ACM and IEEE. He serves as program committee members of top conferences, e.g., NIPS, ICML, AAAI, IJCAI, CIKM, etc. He also serves as reviewers for many top journals, e.g., TiiS, Neurocomp, KBS, FGCS, IJCIS, etc.

Research Interests

Dongsheng Li's research interests focus on key issues in recommender systems, including but not limited to accuracy, efficiency, stability, scalability, privacy and security of collaborative filtering algorithms. Besides, he is also interested to general machine learning applications, including matrix approximation methods, algorithm stability, generalization performance analysis, noise-resilience analysis and graphical models, etc. Meanwhile, he has also been working on data-driven sale science topics with IBM, including up sale, cross sale, opportunity discovery, etc.

Besides computer science, he is also interested to data analysis in smart grid applications, e.g., user appliance usage analysis in smart grid, privacy-preserving smart metering framework design and data-driven fault prognosis and diagnosis in wind turbine and PV systems.

Papers

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.

Working Experience

  • Postdoc Researcher, Tongji University, 2012.9 - 2015.3
  • Research Staff Member, IBM Research - China, 2015.4 - now

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
  • Outstanding Technical Achievement Award, IBM Research, 2019
  • IBM Corperate Award, IBM, 2018
  • Lab Skill Winner, IBM Greater China Group, 2019