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Introduction to Dr.Li Qi

时间:2020-03-18 14:59:26 文章来源 :留学生 浏览量:46

Dr. Li Qi

Dr.Li Qi

Profile

Li Qi received her Ph.D. degree in control science and engineering from Donghua University, Shanghai, China, in 2018. She is currently a lecturer with the Institute of Service Engineering, Hangzhou Normal University, Hangzhou, China. From June 2016 to July 2016, she was a Research Assistant in the Department of Mathematics, Texas A&M University at Qatar, Qatar. From November 2016 to November 2017, she was a Visiting Ph.D. Student in the Department of Computer Science, Brunel University London, U.K. Her current research interests include network communication, complex networks and sensor networks.

Teaching

1.     Data structure, Undergraduate student

2.     Artificial Intelligence,Undergraduate student

Contact Information

School of Information Science and Engineering

Hangzhou Normal University, Hangzhou, China

Email: liqimicky@gmail.com

Project (recent 3 years)

1.     “Distributed state estimation over sensor networks under dynamic event-triggered mechanisms”, Zhejiang Provincial Natural Science Foundation of China, LQ20F030014, 2020-2022, Principle Investigator.

List of Journal papers (recent 3 years)

1.     Qi Li, Bo Shen, Zidong Wang and Weiguo Sheng, Recursive distributed filtering over sensor networks on Gilbert-Elliott channels: A dynamic event-triggered approach, Automatica, 2020.

2.     Qi Li, Zidong Wang, Weiguo Sheng and Nan Li, A dynamic event-triggered approach to recursive filtering for complex networks with switching topologies subject to random sensor failures, IEEE Transactions on Neural Networks and Learning Systems, 2020.

3.     Qi Li, Zidong Wang, Weiguo Sheng, Fawaz E.Alsaadi and Fuad E.Alsaadi, Dynamic event-triggered mechanism for H-infinity non-fragile state estimation of complex networks under randomly occurring sensor saturations, Information Sciences, 2020.

4.     Qi Li, Bo Shen, Zidong Wang, Tingwen Huang and Jun Luo, Synchronization control for a class of discrete time-delay complex dynamical networks: A dynamic event-triggered approach, IEEE Transactions on Cybernetics, 2019.