Haibo He

  • Robert Haas Endowed Professor
  • Electrical, Computer and Biomedical Engineering
  • Phone: 401.874.5645
  • Email: haibohe@uri.edu
  • Office Location: Fascitelli Center for Advanced Engineering, Rm 411
  • Website
  • Google Scholar


  • Computational Intelligence
  • Neural Networks
  • Reinforcement Learning
  • Data Mining


  • Ph.D., Electrical Engineering, Ohio University, 2006
  • M.S., Electrical Engineering, Huazhong University of Science and Technology, Wuhan, 2002
  • B.S., Electrical Engineering, Huazhong University of Science and Technology, Wuhan, 1999

Selected Publications

H. He and E. A. Garcia, “Learning from Imbalanced Data,” IEEE Trans. Knowledge and Data Engineering, Volume 21, Issue 9, pp. 1263-1284, 2009.

H. He, Self-Adaptive Systems for Machine Intelligence, ISBN: 978-0-470-34396-8, Hardcover, Wiley, August, 2011

H. He and X. Zhong, “Learning Without External Reward,” IEEE Computational Intelligence Magazine, Volume: 13, Issue: 3, pp. 48 – 54, Aug. 2018, 2018

H. He and Y. Ma, Editors, Imbalanced Learning: Foundations, Algorithms, and Applications, Wiley-IEEE, ISBN: 978-1-118-07462-6, Wiley-IEEE, July 2013

H. Li, N. Clavette, H. He, “An Analytical Update Rule for General Policy Optimization,” Proceedings of the 39th International Conference on Machine Learning (ICML 2022), Baltimore, Maryland, PMRL 162, 2022.

Recent Grants

6/18/2019. PI. National Science Foundation, “Collaborative Research: Autonomous Hierarchical Adaptive Dynamic Programming for Decision Making in Complex Environment”

Honors and Awards

  • 2018, IEEE Fellow
  • 2017 NSF CAREER Award

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