About
I am a transportation engineering researcher with international academic training and hands-on project experience. My undergraduate journey at Beijing Jiaotong University and Delft University of Technology, advised by Prof. Yonglei Jiang and Prof. Irene Martinez, provided a strong foundation in transportation systems, network modeling, and data-driven analysis. My undergraduate thesis focused on leveraging network topology to predict trip distance distributions (ToD) across China and the Netherlands.
I have led and contributed to projects at the intersection of graph neural networks, intelligent transportation systems, and human-centered mobility, including:
- Driver fatigue detection via EEG-based deep learning with adaptive test-time learning, submitted to IEEE T-ITS, collaborated with the Nanyang Technological University.
- Freight train image recognition at UC Irvine, improving night-time detection accuracy with GIS signal integration.
- AI-based robotics navigation and path planning at Cambridge University.
My experience extends beyond academia. At the Western China Internet of Vehicles and China Merchants Smart City Institute, I worked on vehicle–road–cloud integration, white papers, and large scale urban mobility demonstrations which strengthened my ability to bridge research with practice.
Currently, I am pursuing my MS in Civil & Environmental Engineering at UCLA, advised by Prof. Youngseo Kim. My research focuses on solving design and operational challenges in complex, interconnected transportation and logistics systems, with a special emphasis on human behavior and decision making.
Publications
Review on Short-term Traffic Flow Prediction Methods Under Big Data
International Conference on Mechatronics and Smart Systems (2023). DOI: 10.54254/2755-2721/10/20230183
Proposed a comprehensive review of traffic flow prediction methods under big data; accepted as a conference paper.
Adaptive Test-Time Learning for Driver Fatigue Detection
IEEE Transactions on Intelligent Transportation Systems (under review).
Developed novel test-time adaptation frameworks for EEG-based driver fatigue detection; currently under review.