Kuilin Zhang

Contact
- klzhang@mtu.edu
- 906-487-1828
- Dillman 301i
- Associate Professor, Civil, Environmental, and Geospatial Engineering
- Affiliated Associate Professor, Computer Science
- PhD, Transportation Systems Analysis and Planning, Northwestern University
Biography
Dr. Zhang is Associate Professor in Transportation Systems and Computer Science. Dr. Zhang's research focuses on applying mathematical optimization, control theory, simulation analysis, game theory, machine learning, data science, and on-road vehicle testing to address safety, congestion, energy, environment, and resilience issues of critical civil infrastructure systems in Smart Cities. He advises Ph.D. students from both CEE and CS departments in his research group. Dr. Zhang received his PhD degree in Transportation Systems Analysis and Planning from the Department of Civil, Environmental, and Geospatial Engineering at Northwestern University in December 2009. After working as a Postdoctoral Fellow in the Transportation Center at Northwestern, he joined the Energy Systems Division at Argonne National Laboratory as a Postdoctoral Appointee in November 2010. He is a member of the Editorial Advisory Board of Transportation Research Part E - Logistics and Transportation Review, a member of Transportation Research Board (TRB) standing committees of Transportation Network Modeling (AEP40) and Freight Transportation Planning and Logistics (AT015), and a voting member for the Society of Automotive Engineers (SAE) Cooperative Automation Driving System (CADS) Committee. He is also a member of IEEE, INFORMS, and ITE. Dr. Zhang is a recipient of the NSF CAREER Award in 2019.
Links of Interest
Teaching Interests
- Transportation Network Analysis
- Traffic Flow Theory
- Travel Demand Analysis
- Transportation Systems Operations and Control
- Transportation Planning
- Traffic Engineering
- Optimization Methods
Research Interests
- Data-driven optimization and control models for connected and automated vehicles (CAVs)
- Big traffic data analytics using machine learning
- Mobile and crowd sensing of dynamic traffic systems
- Dynamic network equilibrium and optimization
- Modeling and simulation of large-scale complex systems
- Freight logistics and supply chain systems
- Impact of plug-in electric vehicles to smart grid and transportation network systems
- Interdependency and resiliency of large-scale networked infrastructure systems
- Vehicular Ad-hoc Networks (VANETs)
- Smart Cities
- Cyber-Physical Systems