I am a Ph.D. Candidate and Graduate Research Assistant at the Department of Civil and Environmental Engineering, College of Engineering, Villanova University, PA, USA. I am a member of the Villanova Human Mobility Data Lab (NovaMobility) supervised by Dr. Chenfeng Xiong.

My research focuses on human mobility and large-scale location-based services (LBS) data, with an emphasis on understanding and reconstructing travel trajectories. I develop methods that make noisy movement data analytically usable, ranging from map matching and trajectory reconstruction to the structural modeling of mobility behavior. I am also interested in the broader mobility issues such as accessibility and transit demand–supply mismatches using empirical, high-resolution data.

My current work includes advancing map-matching algorithms for LBS data, particularly NovaMatch, a unified and extensible pipeline capable of matching diverse trajectory and sequence data, including LBS points, TMC paths, and probe traces, to a wide range of transportation networks, as well as developing trajectory modeling frameworks and assessing equity-related mobility outcomes. If you are interested in my research, Feel free to contact me for research discussion and possible collaboration! 😄 🚀 ✨

News

• 10/2025: I will present my paper Rethinking Transit Deserts: Identifying Pseudo and Real Gaps through Trip-Level Mobility Data at the TRB 105th Annual Meeting, as the first presenter in Lectern Session 4018: Evaluation of Non-Conventional Transit Impacts (Wednesday, Jan 14, 8:00–9:45 AM, Room 150B, Convention Center) . The session will be presided by William Wong (Federal Transit Administration).
  Welcome to attend and join the discussion!
• 09/2025: My paper Rethinking Transit Deserts: Identifying Pseudo and Real Gaps through Trip-Level Mobility Data has been accepted by TRB. Another paper, Complete Trip: An Open and Privacy-Safe Dataset of Multimodal Travel Sequences for Urban Transportation Systems Analysis, has also been accepted.
• 08/2025: After the TRB deadline, I’ve been busy “cleaning up” my LBS map-matching code. 🧹 Formatting code so that other humans (including future me) can understand it feels like the hardest optimization problem ever. 🤯 What on earth was I thinking when I wrote this? Now it just looks like a %￥%#@@ ……#…………, completely frazzled… 😵‍💫🔥
• 09/2024: The Computer Software Copyright Registration in China: Vision-Based Lane Detection System With Self-supervised Pre-training Through Masked Sequential Auto-encoders (VLD_SP-MSAE), granted on Sep. 11, 2024, Patent number 2024R11L1180902. And we have published our open source Lane Detection Code on GitHub, including models and dataset.
• 09/2024: I present my recent work: Sup-HMM Map-Matching of Location Data Trajectories: A Heterogeneous and Bayesian-Optimized Hidden Markov Approach at TRC-30 conference. A nice trip on Crete.
• 07/2024: My paper have been submitted and is currently under review by The Transportation Research Board (TRB) 104nd Annual Meeting: Sup-HMM Map-Matching of Location Data Trajectories: A Heterogeneous and Bayesian-Optimized Hidden Markov Approach. Working on the map-matching continues. This work is part of our team’s Complete Trips Project.

• 06/2024: My paper has been accepted by Conference in Emerging Technologies in Transportation Systems (TRC-30): Map Matching of Location Data Trajectories: A Heterogeneous and Bayesian-Optimized Hidden Markov Approach. Very excited for the presentation in Crete, Greece, in September!
• 06/2024: The computer software has been submitted and is currently under review by Computer Software Copyright Registration in China: Lane Line Detection Software Based on Image Sequence Mask Pre-Training.
• 04/2024: My paper has been submitted and is currently under review by Conference in Emerging Technologies in Transportation Systems (TRC-30): Map Matching of Location Data Trajectories: A Heterogeneous and Bayesian-Optimized Hidden Markov Approach. I’m currently working on map matching for human mobility data.
• 10/2023: Two of my TRB papers were accepted:
  • A Novel Highway Traffic Capacity Analyzing Method under Road Region Atmospheric Environment Constraints Based on Computational Fluid Dynamics Model. The Transportation Research Board (TRB) 103rd Annual Meeting. 2023. [Accepted] Rank 1st.
  • Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning. The Transportation Research Board (TRB) 103rd Annual Meeting. 2023. [Accepted] Rank 3rd.
• 09/2023: The article, “The Highway Region Boundary Based on Multi-Environmental Factors,” can now be accessed! View the article here.
• 09/2023: Starting my Ph.D. studies at Villanova University!
• 08/2023: The article, “Robust Lane Detection Through Self Pre-Training With Masked Sequential Autoencoders and Fine-Tuning With Customized PolyLoss,” has been finalized and posted in the “Early Access” area on IEEE Xplore! View the article here.
• 07/2023: I received my Ph.D. offer from Villanova University! Looking forward to new research and life at Villanova!
• 07/2023: My paper Robust Lane Detection through Self Pre-training with Masked Sequential Autoencoders and Fine-tuning with Customized PolyLoss is accepted by the journal of IEEE Transactions on Intelligent Transportation Systems!
• 06/2023: I received my M.Eng. degree in traffic and transportation from Lanzhou Jiaotong University!