Yang Lu

Postdoctoral Scholar
The School of Electrical Engineering and Computer Science
The Pennsylvania State University

Office: 224 Electrical Engineering West, Pennsylvania State University, University Park, PA 16802
Email: yml5046@psu.edu, lubingwu88@gmail.com

Biography

Yang Lu is a postdoctoral scholar advised by Prof. Minghui Zhu in the School of Electrical Engineering and Computer Science at the Pennsylvania State University (PSU). He received Ph.D. degree in Electrical Engineering from PSU in 2020, B.E. and M.E. degrees in Electrical Engineering from Shanghai Jiao Tong University in 2010 and 2013, respectively, and M.S. degree in Electrical Engineering from the Georgia Institute of Technology, in 2013. From January 2019 to May 2019, he worked as a Ph.D. intern at the Pacific Northwest National Laboratory. From March 2013 to June 2014, he worked as a visiting scholar in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He is a recipient of the Dr. Nirmal K. Bose Dissertation Excellence Award at PSU in 2019.

Research Interests

• Cyber-physical privacy and security

• Distributed control and optimization of multi-agent networks

• Machine learning

• Applications: power systems, mobile robotic networks

Journal Papers

[J7] On Privacy-Preserving Cloud Outsourcing of Large-Scale Multi-Agent Quadratic Programs
Yang Lu and Minghui Zhu.
IEEE Transactions on Automatic Control. Submitted.

[J6] Distributed Economic Control of Dynamically Coupled Networks
Yang Lu and Minghui Zhu.
IEEE Transactions on Cybernetics. To appear.

[J5] On Privacy Preserving Data Release of Linear Dynamic Networks
Yang Lu and Minghui Zhu.
Automatica, Volume 115, 2020.

[J4] A Control-Theoretic Perspective on Cyber-Physical Privacy: Where Data Privacy Meets Dynamic Systems
Yang Lu and Minghui Zhu.
Annual Reviews in Control, Volume 47, pages: 423–440, 2019.

[J3] Privacy Preserving Distributed Optimization Using Homomorphic Encryption
(arXiv complete version)
Yang Lu and Minghui Zhu.
Automatica, 96(10): 314–325, 2018.

[J2] Convergence Analysis and Digital Implementation of A Discrete-Time Neural Network for Model Predictive Control
Yang Lu, Dewei Li, Zuhua Xu, and Yugeng Xi.
IEEE Transactions on Industrial Electronics, 61(12): 7035–7045, 2014.

[J1] Convergence Analysis of Discrete-Time Neural Network for Solving Quadratic Programming Problems
Yang Lu, Dewei Li, Yugeng Xi, and Jianbo Lu.
Journal of Systems Science and Mathematical Sciences, 32(11): 1343–1353, 2012.

Conference Papers

[C9] Distributed Safe Reinforcement Learning for Multi-Robot Motion Planning
Yang Lu, Yaohua Guo, Guoxiang Zhao, and Minghui Zhu.
Mediterranean Conference on Control and Automation, 2021. Accepted.

[C8] Secure Perception-Driven Control of Mobile Robots Using Chaotic Encryption
Xu Zhang, Zhenyuan Yuan, Siyuan Xu, Yang Lu, and Minghui Zhu.
American Control Conference, 2021. Accepted.

[C7] Privacy-Preserving Transactive Energy System
Yang Lu, Jianming Lian, and Minghui Zhu.
American Control Conference, pages: 3005–3010, Denver, CO, July, 2020.

[C6] Attack Detection of Nonlinear Distributed Control Systems
Xu Zhang, Yang Lu, and Minghui.
American Control Conference, pages: 1459–1464, Denver, CO, July, 2020.

[C5] Towards A Science for Adaptive Defense: Revisit Server Protection
Zhisheng Hu, Ping Chen, Yang Lu, Minghui Zhu, and Peng Liu.
IEEE International Conference on Collaboration and Internet Computing, pages: 112–121, Pittsburgh, PA, November, 2016.

[C4] Game-Theoretic Distributed Control with Information-Theoretic Security Guarantees
Yang Lu and Minghui Zhu.
IFAC Workshop on Distributed Estimation and Control in Networked Systems, Volume 48, pages: 264–269, Philadelphia, PA, September, 2015.

[C3] Secure Cloud Computing Algorithms for Discrete Constrained Potential Games
Yang Lu and Minghui Zhu.
IFAC Workshop on Distributed Estimation and Control in Networked Systems, Volume 48, pages: 180–185, Philadelphia, PA, September, 2015.

[C2] On Confidentiality Preserving Monitoring of Linear Dynamic Networks Against Inference Attacks
Minghui Zhu and Yang Lu.
American Control Conference, pages: 359–364, Chicago, IL, July, 2015.

[C1] Convergence Analysis of Discrete-Time Simplified Dual Neural Network for Solving Convex Quadratic Programming Problems
Yang Lu, Dewei Li, Yugeng Xi, and Jianbo Lu.
Chinese Control Conference, pages: 3305–3310, Hefei, China, July, 2012.