Zhe Xu is an assistant professor in the School for Engineering of Matter, Transport and Energy at Arizona State University. Before joining ASU, he was a postdoctoral fellow at The Oden Institute for Computational Engineering and Sciences at University of Texas at Austin. He has obtained a PhD degree from the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute in 2018.
The research interests include control theory, machine learning, formal methods and autonomous systems.
Selected Journal Papers
Murat Cubuktepe, Zhe Xu, and Ufuk Topcu, Policy Synthesis of Multi-Agent Systems With Graph Temporal Logic Specifications, IEEE Transactions on Control of Network Systems, 2021.
Bo Wu, Steven Carr, Suda Bharadwaj, Zhe Xu, and Ufuk Topcu, Resilient Distributed Hypothesis Testing With Time-Varying Network Topology, IEEE Transactions on Automatic Control, Regular paper, 2021.
Bo Wu, Murat Cubuktepe, Franck Djeumou, Zhe Xu, and Ufuk Topcu, Switched Linear Systems Meet Markov Decision Processes: Stability Analysis and Policy Synthesis, Conditionally accepted, IEEE Transactions on Automatic Control, 2021.
Zhe Xu, Bo Wu, and Ufuk Topcu, Control Strategies for COVID-19 Epidemic with Vaccination, Shield Immunity and Quarantine: A Metric Temporal Logic Approach, PLOS ONE, 2021.
Ruixuan Yan, Zhe Xu and Agung Julius, Swarm Signal Temporal Logic Inference for Swarm Behavior Analysis, IEEE Robotics & Automation Letters, vol. 4 (3), pp. 3021 - 3028, July, 2019.
Selected Conference Papers
Jean-Raphaël Gaglione, Daniel Neider, Rajarshi Roy, Ufuk Topcu, Zhe Xu, Learning Linear Temporal Properties from Noisy Data: A MaxSAT Approach, The 19th International Symposium on Automated Technology for Verification and Analysis (ATVA), 2021, regular paper, acceptance rate 25.3%.
Zhe Xu, Bo Wu, Aditya Ojha, Daniel Neider, Ufuk Topcu, Active Finite Reward Automaton Inference and Reinforcement Learning Using Queries and Counterexamples, International IFIP Cross Domain (CD) Conference for Machine Learning & Knowledge Extraction (MAKE), 2021.