Ph.D. Positions in Sustainable and Intelligent Transportation Systems at Michigan Tech
Prospective students are expected to work in the high-performance computing Laboratory on Sustainable and Intelligent Transportation Systems (SITS-Lab) with Dr. Kuilin Zhang. Dr. Zhang is Assistant Professor in the Department of Civil and Environmental Engineering (CEE) at Michigan Technological University (Michigan Tech), Houghton, Michigan, U.S.A. Dr. Zhang received his Ph.D. degree 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. Dr. Zhang is a member of the Editorial Advisory Board of Transportation Research Part E - Logistics and Transportation Review, as well as Transportation Research Board (TRB) standing committees of Transportation Network Modeling (ADB30) and Freight Transportation Planning and Logistics (AT015). Dr. Zhang's research areas include transportation network modeling and optimization, intelligent transportation systems, logistics and supply chain systems, travel behavior, traffic flow theory, travel demand analysis, and plug-in electric vehicles.
Interested applicants from transportation engineering, applied mathematics, systems engineering, control theory, and computer science are encouraged to contact Dr. Zhang directly by sending a complete resume, research statement, and representative publications at klzhang@mtu.edu, and submit their applications FREE on-line at http://www.mtu.edu/cee/graduate/civil/. You are expected to have a passion for transportation research, solid mathematics background such as operations research, control theory, and statistical models, and proficient programming skills in languages such as C++ and Java.
根据您的兴趣爱好和背景情况,未来您或者参加一个NSF的项目 - Improving Spatial Observability of Dynamic Traffic Systems through Active Mobile Sensor Networks and Crowdsourced Data;或者,您会参加一个US DOT和Argonne National Laboratory合作的公交系统应急管理的项目。这两个项目主要用到优化模型,控制理论,以及计算机科学的知识,来研究如何观测或监测动态交通流,或者优化公交系统进行应急管理。另外的研究方向是交通大数据,connected and automated vehicles, data-driven robust optimization, hybrid CPU and GPU computing.