Zhaojian Li

Zhaojian Li 
  • Zhaojian Li, Ph.D.

  • Director, Robotics and Intelligent Vehicle Automation Lab (RIVAL)

  • 428 S Shaw Lane, East Lansing, MI 48824

  • Tel: (+1)-517-432-1821

News

  • 02/2023: Our project on "Integrated Design and Efficient Safe Control for Terrain-Adaptive Ultra-lightweight Vehicles" has been funded by Army.

  • 10/2022: I gave an invited talk on "PowerNet: Deep Multi-agent Reinforcement Learning for Scalable Powergrid Control" at 2022 INFORMS.

  • 10/2022: I gave a seminar on "Internet of Mobility: Cloud-Facilitated Privacy-Aware Collaborative Sensing and Controls" at University of Texas at Austin.

  • 08/2022: Our project FRR: Collaborative Research: Collaborative Learning for Multi-robot Systems with Model-enabled Privacy Protection and Safety Supervision has been funded by National Science Foundation. This is a collabration with Prof. Yongqiang Wang at Clemson University.

  • 08/2022: I gave a seminar on "Internet of Mobility: Cloud-Facilitated Privacy-Aware Collaborative Sensing and Controls" at National University of Singapore.

  • 07/2022: I gave a talk on "Efficient and Privacy-Preserving Data-Enabled Predictive Control for Electric Vehicles" at Ford Motor Company.

  • 06/2022: Kaian Chen successfully defended his PhD dissertation and he is joining Ford Motor Company. Congratulations, Kaian!

  • 06/2022: Our STTR project on Wide-area Advanced Synthetic Skin with Enhanced Sensory Perception for Low-Visibility Undersea Environments has been funded by Office of Naval Research.

  • 11/2021: My NSF CAREER project is featured on MSUToday.

  • 08/2021: Kyle Lammers won 2021 MTRAC AgBio Innovation Challenge Award. Congratulations Kyle!

  • 08/2021: Our STTR project on Multi-Modal Cloud Based System for Detecting Early Signs of Driver Cognitive Decline and/or High Risk Driving Behaviors has been funded by National Institute of Health.

  • 07/2021: Our project on Deep Learning-Based Robust 3D Apple Tree Perception through Efficient Multi-Sensor Fusion by US Department of Agriculture.

  • 04/2021: Our project on CAREER: Cloud-facilitated Privacy-aware Collaborative Sensing and Control for Intelligent and Connected Vehicles has been funded by National Science Foundation.

  • 02/2021: Our project on Learning-Empowered Automated Phone Testing has been funded by T-Mobile USA Inc.

  • 11/2020: Our project on Multi-Arm Soft Robots is featured at MSUToday.

  • 08/2020: Our project "NRI: INT: SMART: Soft Multi-Arm RoboT for Synergistic Collaboration with Humans" has been Funded by National Science Foundation.

  • 08/2020: Our project "Development of a Control and Planning System for an Apple Robotic Harvester" has been Funded by US Department of Agriculture.

  • 08/2020: Our project "Collaborative Research: Road Information Discovery through Privacy-Preserved Collaborative Estimation in Connected Vehicles" has been supported by National Science Foundation.

  • 09/2019: Our project "Robotic Apple Harvesting" has been supported by US Department of Agriculture.

  • 08/2019: I gave a keynote talk at the 2019 China Process Control Conference in Kunming.

  • 06/2019: Our project "Road information harvesting: using cars as mobile sensors" has been funded by DENSO Foundation.

  • 04/2019: Our project "Adaptive vehicle control through clustering based system identification and model predictive control" has been funded by Ford-MSU Alliance project.

  • 08/2018: Our project "Cloud-based driving monitoring and analytics" has been funded by Michigan Economic Development Corporation.

  • 06/2018: I presented 2 papers and co-chaired 3 sessions at 2018 American Control Conference in Milwaukee.

  • 05/2018: I gave a talk on Dynamic Modeling and Control with Real-Time Learning at General Motors.

  • 04/2018: We have successfully hosted the 7th Midwest Workshop on Control and Game Theory at MSU.

  • 03/2018: I have been invited to serve as Associated Editor and program committee member for the 2018 ASME Dynamic System and Control Conference.

  • 01/2018: Our paper on Decentralized Fault Prognosis of Discrete-Event Systems Using State-Estimate-Based Protocols has been accepted by IEEE Transactions on Cybernetics.

  • 12/2017: I have been invited to serve as a Program Committee member at IJCAI-ECAI 2018.

  • 12/2017: I gave a talk at West Sydney University.

  • 12/2017: Our project "Online engine system identification with evolving spatial-temporal filters" has been funded by Ford Motor Company.

  • 12/2017: I gave a talk at Siemens PLM, Livonia, Michigan.

  • 10/2017: I gave a talk at the Control Seminar at the University of Michigan, Ann Arbor.

  • 10/2017: Our paper on Training Drift Counteraction Optimal Control Policies Using Reinforcement Learning: An Adaptive Cruise Control Example has been accepted by IEEE Transactions on Intelligent Transportation System.

  • 09/2017: Our paper on Visual-Manual Distraction Detection Using Driving Performance Indicators with Naturalistic Driving Data has been accepted by IEEE Transactions on Intelligent Transportation System.

  • 09/2017: Our paper on Infinite-Step Opacity of Stochastic Discrete-Event Systems has been accepted by 2017 Asian Control Conference.

  • 09/2017: Our paper on Cloud Resource Allocation for Cloud-Based Automotive Applications has been accepted by Mechatronics.

  • 08/2017: I have been invited as a member in the International Program Committee for the 5th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, E-CoSM 2018.

  • 07/2017: I served as a penalist at the 2017 AIAA Intelligent Systems Workshop in the Self-Driving Cars session.

  • 05/2017: I co-chaired the session "Autonomous and Assisted Driving I" in the 2017 American Control Conference.

  • 05/2017: Our book chapter on H-infinity Filtering for Cloud-Aided Semi-active Suspension with Delayed Information published with Springer is now online.

  • 01/2017: I have been invited to be a member of the IEEE Control Systems Society Technical Committee on Discrete-Event Systems.

  • 11/2016: Our paper on distributed state estimation of sensor network systems subject to Markovian channel switching with an application to a chemical process has been accepted by IEEE Transactions on Systems, Man, and Cybernetics.

  • 10/2016: Our paper on optimal state estimation for systems driven by jump-diffusion process with application to road anomaly detection has been accepted by IEEE Transactions on Control System Technology.

  • 09/2016: Our paper on a new clustering algorithm for processing GPS-based road anomaly reports has been accepted by IEEE Transactions on Intelligent Transportation Systems.

  • 07/2016: Our paper on road disturbance estimation and cloud-aided comfort-based route planning has been accepted by IEEE Transactions on Cybernetics.

  • 07/2016: I presented two papers at ACC 2016, Boston, USA.

  • 02/2016: Our paper on fault prognosis has been accepted by Automatica.

  • 01/2016: I started my career at General Motors as an algorithm design and development engineer .

  • 12/2015: Two of my paper were presented at CDC, Osaka, Japan.

  • 12/2015: I defended my Ph. D. dissertation "Developments in Estimation and Control for Cloud-Enabled Automotive Vehicles".

  • 11/2015: Our paper on reliable decentralized fault prognosis of discrete-event systems has been accepted by IEEE Transactions on Systems.

  • 10/2015: Our paper on road risk modeling and cloud-aided safety-based route planning has been accepted by IEEE Transactions on Cybernetics.

  • 07/2015: I presented a paper at ACC 2015, Chicago, USA.

  • 12/2014: I presented a paper at IEEE Symposium on CIVTS 2014, Orlando, USA.

  • 10/2014: I presented a paper at IEEE Conference on SMC 2014, San Diego, USA.