Lu Feng
University of Virginia
I am an Assistant Professor at the Department of Computer Science and the Department of Engineering Systems and Environment at the University of Virginia (UVa). I am also a member of the Link Lab - the center of research excellence in Cyber-Physical Systems at UVa. Previously, I was a postdoctoral fellow at the University of Pennsylvania. I hold a PhD in Computer Science from the University of Oxford, a M.Phil. in Computer Speech, Text and Internet Technology from the University of Cambridge, and a B.Eng. in Information Engineering from the Beijing University of Posts and Telecommunications.
My research focuses on assuring the safety and trustworthiness of cyber-physical systems (CPS). I develop modeling and analysis methods for CPS, drawing on formal methods, machine learning, control theory, and human factors. I also work across many different application domains, from autonomous robots, to smart cities, to medical systems. I have been fortunate to receive a couple of awards for my work, including NSF CAREER Award, NSF CRII Award, among others.
Recent News
Mar. 2021: Our paper “A Novel Spatial-Temporal Specification-Based Monitoring System for Smart Cities” has been accepted for publication at the IEEE Internet of Things Journal (impact factor: 11.7).
Dec. 2020: Our paper “Safe Multi-Agent Reinforcement Learning via Shielding” has been accepted for publication at the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021) (acceptance rate: 25%).
Dec. 2020: Our paper “DeepTake: Prediction of Driver Takeover Behavior using Multimodal Data” has been accepted for publication at the ACM Conference on Human Factors in Computing Systems (CHI 2021) (acceptance rate: 25%).
Dec. 2020: Our paper “Trust-Based Route Planning for Automated Vehicles” has been accepted for publication at the ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS 2021) (acceptance rate: 26%).
Nov. 2020: Our research team has won the NIH-organized NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research.
Sep. 2020: Our paper “STLnet: Signal Temporal Logic Enforced Multivariate Recurrent Neural Networks” has been accepted for publication at the Thirty-fourth Conference on Neural Information Processing Systems (NeurlPS 2020) (acceptance rate: 20%).
Contact
Office: Olsson Hall, Room 271
Phone: 434-982-2388
Email: lu.feng at virginia dot edu