Haibo He, Ph.D., P.E.                                 
 IEEE Fellow
 Department Chair
 Robert Haas Endowed Chair Professor

 IEEE Trans. on Neural Networks and Learning Systems

 Computational Intelligence and Self-Adaptive Systems Laboratory


Department of Electrical, Computer, and Biomedical Engineering

Pastore 126, 51 Lower College Road
University of Rhode Island
Kingston, RI 02881
Tel:   (401) 874-5844; Fax:  (401) 782-6422        
Email: haibohe@uri.edu

Welcome to the Computational Intelligence and Self-Adaptive Systems (CISA) Laboratory!

  • Senior Design Project Day
  • Chairing ISNN 2009
  • ICNSC 2010 in Chicago
  • IEEE CIS 2014 Workshop at URI
  • IEEE CIS Outstanding Career Award2014
  • ISNN Conference
  • Faculty vs Grads 2015 annual game
  • PBN Award Ceremony
  • Award Ceremony in NYC
  • Christmas Party 2014
  • In Preparation for PhD Qualify Exam
  • wowslideshow
  • Zhen Ni Recevies Prestigous Chinese Government Award
Senior Design Project Day1 Chairing ISNN 20092 ICNSC 2010 in Chicago3 IEEE CIS 2014 Workshop at URI4 IEEE CIS Outstanding Career Award20145 ISNN Conference6 Faculty vs Grads 2015 annual game7 PBN Award Ceremony8 Award Ceremony in NYC9 Christmas Party 201410 In Preparation for PhD Qualify Exam11 Students in Chat - Thanksgiving Party12 Zhen Ni Recevies Prestigous Chinese Government Award13
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Photo courtesy: CISA Lab  


  * New: RA available in 2018* [Click here...] 
  • 2018-10-20:  Haibo delivers a keynote talk "Learning: From Shallow to Deep" at the Symposium on Computational Intelligence in Qingdao, Shandong.

  • 2018-09-20:  IEEE Control Systems Magazine interview: People in Control  [Link]

  • 2018-09-15:  Haibo delivers a Keynote Talk at the 6th Annual IEEE North Jersey Advanced Communications Symposium (NJACS-2018).

  • 2018-09-01:  IEEE Smart Grid Newsletter: "Cyber-Physical Resilience of the Smart Grid: Challenges and Opportunities." [Link]

  • 2018-08-23:  Haibo delivers a Keynote Talk at the 2018 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC 2018).

  • 2018-08-23:  Congratulations to Yazhou for finishing his M.S. defense. Yazhou will be joining Leviton in Long Island, New York.

  • 2018-07-18:  Haibo delivers a Keynote Talk at the "AI Frontiers" conference in Changsha, Hunan.

  • 2018-07-01:  Haibo receives an ONR grant.

  • 2018-06-07:  Haibo delivers a Keynote Talk at the "Workshop on Artificial Intelligence in the Era of Big Data" in Hongkong.

  • 2018-05-20: Congratulations to Jun Yan for receiving the 2018 URI Graduate School Excellence in Doctoral Research Award.. [Link]

  • 2018-05-01: Congratulations to Xiangnan Zhong for receiving the 2017 "Chinese Government Award for Outstanding Student Abroad". [Link]

  • 2018-04-10: Haibo serves as a member of the IEEE Computer Society Fellows Committee;

  • 2018-04-01: Haibo serves as a member of the IEEE Computational Intelligence Society (CIS) Fellows Committee;

  • 2018-03-28: Haibo delivers a Tutorial Talk at the 10th International Conference on Advanced Computational Intelligence (ICACI 2018) in Xiamen.

  • 2018-02-12: Haibo Co-organizes the NSF workshop on Real-time Learning and Decision Making in Dynamical Systems. [Link]

  • 2018-01-10: Haibo and Bo Tang receives the IEEE 8th IEEE Annual Computing and Communication Workshop and Conference (IEEE CCWC'18) Best Paper Award.

  • 2017-12-01: Haibo was elected to be an IEEE Fellow. [Link]

  • 2017-08-10: Haibo receives NSF grant to develop new neuromorphic computing and machine learning approaches for spectrum and energy-efficient wireless networks.

  • 2017-08-01: A reunion of the CISA alumni in Anchorage, Alaska: "From 5 Students to 5 Assistant Professors" [Picture: left to right: Bo Tang (Mississippi State University), Jun Yan (Concordia University), (^_^), Xiangnan Zhong (University of North Texas), Zhen Ni (South Dakota State University), Yufei Tang (Florida Atlantic University)].

  • 2017-07-27:  Paper entitled "Dampling Control Design for Pulse Width Modulation Series Compensator Using GrHDP" won the First Place in the 2017 IEEE PESGM Graduate Student Category Poster Competition!

  • 2017-06-09: Media report: "How to Better Harness the Power of the Wind" [Link].

  • 2017-05-29:  Haibo delivers a Keynote Talk at the 29th Chinese Control and Decision Conference (CCDC'17) in Chongqing, China.

  • 2017-05-10:  Congratulations to Jun Yan for accepting a tenure-track Assistant Professor position at the Concordia University, Montreal, Canada.

  • 2017-05-08:  Congratulations to Xiangnan Zhong for accepting a tenure-track Assistant Professor position at the University of North Texas, Denton, TX.

  • 2017-05-05:  Congratulations to Jun Yan for successfully defending her Ph.D. dissertation!

    [More news >>>]

    Media Highlight:

    [PBN "Rising Star Innovator" Award and Interview]: FORWARD THINKING: Haibo He, a researcher at the University of Rhode Island, College of Engineering, is leading a team that specializes in artificial intelligence and machine learning attempt to have computers mimic the human brain. This interview highlights some of Haibo and his group's research on computational intelligence, adaptive systems, and their applications. [Read more >>>].

    Research Highlight:

    [Smart Grid]: Growing energy demands and environmental concerns have significantly increased the interest of smart grid. The CISA group has been focused on several critical aspects of smart grid research, including: intelligent power grid control and optimization, renewable energy, and smart grid security (both cyber security and physical failures of the grid). This research will contribute to developing intelligent, robust, secure, and reliable future smart grid systems. [Read more >>>].

    Publication Highlight:

    H. He and E. A. Garcia, "Learning from Imbalanced Data," IEEE Trans. Knowledge and Data Engineering, vol. 21, issue 9, pp. 1263-1284, 2009 [pdf].  [The Most-Cited paper in the IEEE TKDE since 2009 to date]


    [Big Data]: With the continuous expansion of data availability in many complex systems, it becomes critical to advance the fundamental research of intelligent data analysis. This Survey Paper provides a comprehensive and critical review of Imbalanced Learning, including the foundation and nature of the problem, state-of-the-art techniques, assessment metrics, as well as future research opportunities and directions on Imbalanced Learning. [Read more >>>].

    We gratefully acknowledge the support from: