Haibo He’s Research Profile

Recent Grants¹

Grant
7/12/2020. Co-PI. Navatek, US Office of Naval Research. “RE-ROUTE: Network Cyber-Physical Security and Resiliency”
1/29/2019. PI. US Office of Naval Research. “Toward a Reliable and Resilient Smart Grid: From Early Detection to Grid Behavior Analysis.”
1/7/2019. PI. US Office of Naval Research. “Toward a Reliable and Resilient Smart Grid: From Early Detection to Grid Behavior Analysis.”
5/2/2018. PI. US Office of Naval Research. “Toward a Reliable and Resilient Smart Grid: From Early Detection to Grid Behavior Analysis.”
8/7/2017. PI. National Science Foundation. “Collaborative Research: Enabling Dynamic Spectrum Access for Future Broadband Wireless Networks Using Neuromorphic Computing.”
3/22/2017. Co-PI. US Department of Interior. “CI – Electromagnetic Field Impacts on Elasmobranch (Sharks, Rays, and Skates) and American Lobster Movement and Migration from Direct Current Cables.”

Citation
Li H, Clavette N, He H. An Analytical Update Rule for General Policy Optimization. International Conference on Machine Learning, 2022; 12696-12716.
He Haibo, Jiang H. Deep Learning based Energy Efficiency Optimization for Distributed Cooperative Spectrum Sensing, IEEE Wireless Communications, 2019; 26(3), 32-39. doi: 10.1109/MWC.2019.18003972
He H, Zhong X. Learning without external reward. IEEE Computational Intelligence Magazine, 2018; 13(3), 48-54. doi: 10.1109/MCI.2018.2840727
Ma Y, He H. Imbalance learning: foundations, algorithms, and applications. John Wiley & Sons, 2013.
He H. Self-adaptive systems for machine intelligence. John Wiley & Sons, 2011.
He H, Garcia EA. Learning from imbalanced data. IEEE Transactions on knowledge and data engineering, 2009; 21(9), 1263-1284. doi: 10.1109/TKDE.2008.239