About Me
I am Chenxi Liu (刘晨曦), and you may also call me Dylan. I am an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Utah. I earned my Bachelor’s degree in Civil Engineering from Tsinghua University in 2017, and completed my MS and Ph.D. degree in Civil and Environmental Engineering at the University of Washington in 2020 and 2024, respecitively.
My research focused on the situation-aware customized machine intelligence to establish a connected and autonomous transportation system for safety, equity, and resiliency. More specifically, I prefer to develop advanced machine intelligence with Generative Artificial Intelligence and Distributed Learning Structure to build a connected and autonomous transportation system for various applications.
🚀️Funded Ph.D. Student Positions Are Opening!!!🚀️
I am pleased to offer fully funded Ph.D. positions starting from Autumn 2026 in the Department of Civil and Environmental Engineering at University of Utah. Candidates will engage in cutting-edge research focused on customizing machine intelligence within the field of intelligent transportation. Key areas of research will include, but are not limited to:
- Integrated sensing technologies
- Cyber-physical cooperation
- Distributed computing
- Predictive control methods
- Generative Artificial Intelligence
If you are passionate about these research areas and enjoy living in Salt Lake City, which offers world-class skiing and numerous amazing national parks, I would be delighted to consider you for our team at University of Utah. Dedicated research experience or background is NOT required. We are looking for candidates who are driven by passions for the field and a commitment to long-term goals. Together, we can develop our research expertise.
Please send your transcript and CV to me at chenxi.liu@utah.edu. Let’s join forces and make a significant impact while having fun along the way!😄
Undergraduate/graduate visitors are also welcome.
🎉️ News
- New! Aug. 2025. The University of Utah Transportation Team, in collaboration with the Utah Department of Transportation, has been selected as one of the three finalists in the National Operations Center of Excellence (NOCoE) Transportation Technology Tournament (TTT) . We will present our project at the ITE Annual Meeting on August 11, 2025.
- New! July. 2025. The University of Utah Transportation Electrification Certificate Program cooperating with Utah State University has received additional funding in the following two years from Utah System of Higher Education (USHE) Deep Tech Initiative.
- New! Jun. 2025. Our new paper, “LangCoop: Collaborative Driving with Language,” co-authored with the cooperators at Texas A&M University, received the Best Paper Award at the IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) 2025, Workshop on Multi-agent Embodied Intelligent Systems.
- New! Jun. 2025. Our lab is excited to partner with the University of Utah High School Summer Research Internship 2025 and welcome three K–12 students, Lucas, Isabel, and Weijia, as summer interns. We’re thrilled to have them join us for a summer of learning and discovery!
- New! May. 2025. Ph.D. student, Fengze Yang, received a $1,000 scholarship to support his presentation in the Mountain District ITE Conference.
- New! May. 2025. Our new research paper “A Self-Supervised Multi-Agent Large Language Model Framework for Customized Traffic Mobility Analysis Using Machine Learning Models” is accepted and published on Transportation Research Record.
- New! Apr. 2025. Ph.D. student, Xuewen Luo, has been selected for the 2025 IEEE Intelligent Transportation Systems Society (ITSS) Fellowship Program for Promoting Women, Young Professionals, and Leadership in ITS. As part of the program, she organized and hosted a workshop in June titled “Ask Her Way: A Reverse Q&A and Career Match for Aspiring Women in Transportation.”
- New! Apr. 2025. Our new paper “Attention-Based Feature Fusion Empowered Encoder-Decoder Framework for Nighttime Traffic Perception From High-Altitude Surveillance System” is accepted and published on IEEE Transaction on Intelligent Transportation Systems (IEEE-ITS).
- New! Apr. 2025. Our new paper “Mitigating biases in big mobility data: a case study of monitoring large-scale transit systems” is accepted and published on Transportation Letters.