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Zhiyi Li
PeerJ Editor
400 Points

Contributions by role

Editor 400

Contributions by subject area

Security and Privacy
Neural Networks
Data Mining and Machine Learning
Artificial Intelligence
Natural Language and Speech
Distributed and Parallel Computing
Network Science and Online Social Networks

Zhiyi Li

PeerJ Editor

Summary

Dr. Zhiyi Li received his Ph.D. degree in Electrical Engineering from Illinois Institute of Technology in 2017. He received an M.E. degree in Electrical Engineering from Zhejiang University (Hangzhou, China) in 2014 and a B.E. degree in Electrical Engineering from Xi’an Jiaotong University (Xi’an, China) in 2011. From August 2017 to May 2019, he was a senior research associate at Robert W. Galvin Center for Electricity Innovation at Illinois Institute of Technology. Since June 2019, he has been with the College of Electrical Engineering, Zhejiang University(Hangzhou, China) as a research professor. His research interests lie in the application of state-of-the-art optimization and control techniques in smart grid design, operation and management with a focus on cyber-physical security. He has already authored/co-authored over 60 refereed journal articles in these areas. He is an associate editor of 4 other international journals (IEEE Access, Journal of Modern Power Systems and Clean Energy, Journal of Electrical Engineering and Technology, and IET Journal of Engineering) and a reviewer of over 30 international journals (including IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, IEEE Transactions on Sustainable Energy, and IEEE Transactions on Power Delivery).

Agents & Multi-Agent Systems Algorithms & Analysis of Algorithms Data Mining & Machine Learning Security & Privacy

Editorial Board Member

PeerJ Computer Science

Work details

Research Professor

Zhejiang University
June 2019
Electrical Engineering

Websites

  • Google Scholar

PeerJ Contributions

  • Edited 3

Academic Editor on

December 4, 2023
Detecting anomalous electricity consumption with transformer and synthesized anomalies
Tianshi Mu, Yun Yu, Guocong Feng, Huan Luo, Hang Yang
https://doi.org/10.7717/peerj-cs.1721
August 2, 2022
Privacy-preserving household load forecasting based on non-intrusive load monitoring: A federated deep learning approach
Xinxin Zhou, Jingru Feng, Jian Wang, Jianhong Pan
https://doi.org/10.7717/peerj-cs.1049
March 9, 2021
Effects of network topology on the performance of consensus and distributed learning of SVMs using ADMM
Shirin Tavara, Alexander Schliep
https://doi.org/10.7717/peerj-cs.397