PhD Scholarships

Multiple Ph.D. Research Assistant Scholarships on Connected and Automated Vehicles (CAVs), Intermodal Logistical Modeling, and Railroad Systems Modeling at Michigan Tech (2024/2025)

 

Multiple Ph.D. Research Assistant Scholarships are available at Michigan Tech. Prospective students will work on projects in the following three areas.

(1)    Connected and automated vehicles (CAVs):  Students will work on research on modeling and on-road testing vehicular ad-hoc network (VANET) systems with C-V2X onboard units (OBUs) and roadside units (RSUs). Students with backgrounds and interests are preferred in wireless network communication, optimization, automation, control, machine learning, data analytics, real-time systems, hardware-in-the-loop, systems integration, and software development. We are interested in students from the Departments of Automation Engineering, Electrical Engineering, Computer Engineering, Telecommunication Engineering, Computer Science, Systems Engineering, Automotive Engineering, and Intelligent Transportation Systems. Students are expected to build software systems using C++ in Linux and travel to testing facilities to test connected and automated vehicles in the real world.

(2)    Intermodal logistical modeling: Students will work on intermodal (maritime, rail, and truck) logistics modeling, freight network modeling (e.g., routing and scheduling, network resilience), intermodal freight network simulation, freight demand modeling, renewable energy consumptions modeling for transportation, EV charging behavior using queueing theory, decision-making under uncertainty, distributionally robust optimization, cooperative decision-making automation, Graph Neural Networks (GNN), data analytics, and software development. We are interested in students from the Departments of Industrial Engineering, Systems Engineering, Transportation Engineering, Logistics Engineering, Applied Mathematics, and Computer Science. Students are expected to develop mathematical models and software systems using C++ in Windows.

(3)    Railroad Systems Modeling: Students will work on railroad systems modeling, train control and communications, highway-rail connectivity, rail intermodal terminal optimization, train estimate time arrival, timetabling, positive train control, train platooning, and rail capacity analysis using optimization, simulation, and machine learning. We are interested in students from the Departments of Transportation Engineering, Industrial Engineering, Systems Engineering, Applied Mathematics, Computer Science, and Electrical Engineering. Students are expected to develop mathematical models and tools using Python or C++ programming.

 

Students are expected to work in the high-performance computing Laboratory on Sustainable and Intelligent Transportation Systems (SITS-Lab) with Dr. Kuilin Zhang. In the Transportation Systems area, Dr. Zhang's research focuses on transportation network modeling and optimization, Intelligent Transportation Systems, logistics and supply chain systems, traffic flow theory, traffic simulation, mobile sensing, big traffic data analytics, connected and automated vehicles, and plug-in electric vehicles. In the Computer Science area, Dr. Zhang's research focuses on Vehicular Ad-hoc Networks (VANETs), the Internet of Things (IoT), Cyber-Physical Systems (CPS), High-Performance Computing, Real-time Systems, Deep Reinforcement Learning (DRL), GNN, and Real-Time Machine Learning. Interested applicants from transportation engineering, applied mathematics, systems engineering, automation, communication, control theory, electrical and computer engineering, and computer science are encouraged to contact Dr. Zhang directly by sending a complete resume, transcripts, research statement, and representative publications to klzhang@mtu.edu, and submit their applications online at https://www.mtu.edu/cege/graduate/civil . You are expected to have

 

Dr. Kuilin Zhang is an Associate Professor in the Department of Civil, Environmental, and Geospatial Engineering (CEGE) in the College of Engineering and an Affiliated Associate Professor in the Department of Computer Science (CS) in the College of Computing at Michigan Tech, Houghton, Michigan, U.S.A. Dr. Zhang is also a faculty affiliate of the Michigan Tech Transportation Institute (MTTI), the Institute of Computing and Cybersystems (ICC), and the Power Systems Engineering Research Center (PSERC). Dr. Zhang received his Ph.D. in Transportation Systems Analysis and Planning from the Department of Civil and Environmental 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 joined Michigan Tech in August 2013. Dr. Zhang has been a member of the Transportation Research Board (TRB) standing committees of Transportation Network Modeling (AEP40), Freight Transportation Planning and Logistics (AT015), and Railroad Operating Technologies Committee (AR030), as well as a voting member of the Society of Automotive Engineers (SAE) Cooperative Driving Automation (CDA) Committee and BSM Task Force. He is also a member of IEEE, INFORMS, and ITE. Dr. Zhang's research has been supported by the National Science Foundation (NSF), the Department of Energy (DOE), the Department of Transportation (DOT), and the Michigan DOT (MDOT). He and his student also received the 2022 Gartner Prize for the "Best Paper on Traffic Flow Theory" from TRB ACP50 Traffic Flow Theory and Characteristics Committee. Dr. Zhang was a recipient of the NSF CAREER Award in 2019.