Lei Lin

Lei Lin’s research interests include Transportation Big Data, Connected and Automated Vehicle and Machine Learning. Prior to joining the University of Rochester, Lei worked as a research associate at Center for Connected and Automated Transportation (CCAT) at Purdue University, where he led a project about Human-driven Vehicle Trajectory Prediction for Connected and Automated Vehicle Platoon Control. Before that, Lei was a researcher at Conduent/PARC/Xerox from 2015 to 2017, where he worked on connected vehicle and transportation energy optimization projects.

Lei Lin holds a Ph.D. degree in Civil Engineering and an M.S. degree in Computer Science, both from University at Buffalo, the State University of New York. He has published more than 35 peer-reviewed journal and conference papers.

Publications:

Lei Lin, Beilei Xu, Wencheng Wu, Trevor W. Richardson, and Edgar A. Bernal.  “Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 83-86. 2019.

Li, Tao, and Lei Lin. “AnonymousNet: Natural face de-identification with measurable privacy.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 0-0. 2019.

Ren, Shuyun, Fengji Luo, Lin Lei, Shu-Chien Hsu, and Xuran Ivan Li. “A novel dynamic pricing scheme for a large-scale electric vehicle sharing network considering vehicle relocation and vehicle-grid-integration.” International Journal of Production Economics (2019).