Qianwen Li, Ph.D.

Assistant Professor

Intelligent Transportation Systems

Dr. Qianwen (Cami) Li is an Assistant Professor in the School of Environmental, Civil, Agricultural and Mechanical Engineering (ECAM) at the University of Georgia. Dr. Li leads the Cooperative Automated Mobility Innovations (CAMIs) Lab. Her research aims to identify issues with existing transportation systems, propose innovative solution methods to approach these issues with emerging technologies (such as vehicle communication, automation, electrification, and smart infrastructure), and then test and evaluate the proposed methods in the real world. The goal is to help build a greener, safer, more efficient, more sustainable, and more equitable future transportation system. Her works have been published by top transportation journals, such as Transportation Research Part E, Transportation Research Part D, Accident Analysis & Prevention, and IEEE Transactions on Intelligent Transportation Systems.

Education
  • Ph.D., University South Florida, Civil Engineering (Transportation), 2020 – 2022
  • M.S., University South Florida, Civil Engineering (Transportation), 2018 – 2020
  • B.Eng., Shandong University, China, Computer Science and Technology, 2014 – 2018
Professional Appointments
  • Assistant Professor, School of Environmental, Civil, Agricultural and Mechanical Engineering, University of Georgia, 2023 – Present
  • Assistant Research Professor, Center for Urban Transportation Research, University of South Florida (USF), 2022 – 2023
  • Honorary Associate, Department of Civil and Environmental Engineering, University of Wisconsin-Madison, 2022 – 2023
  • Graduate Research Assistant, CEE, USF, 2018 – 2022
Awards & Honors
  • Council of University Transportation Centers (CUTC): Milton Pikarsky Memorial Award for the best doctoral dissertation in the field of science and technology in transportation studies, 2023.
  • Council of University Transportation Centers (CUTC): Neville A. Parker Award for the best non-thesis master’s project reports in the field of Science and Technology, 2022.
Areas of Expertise
  • Traffic Data Collection and Analysis
  • Connected and Autonomous Vehicle Modeling, Development, and Field Experiments
  • Smart City Infrastructure Systems
  • Machine Learning
  • Transportation Safety
Publications

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