I am a Ph.D. Candidate in Civil and Environmental Engineering at Villanova University and a member of the NovaMobility advised by Dr. Chenfeng Xiong.

My research lies at the intersection of human mobility science, spatial–temporal data modeling, and computational infrastructure design. I study how large-scale location-based service (LBS) data can be structurally represented, reconstructed, and reasoned about to enable reliable behavioral and transportation intelligence.

Rather than treating trajectories as raw sequences of points, I develop foundational representations and modeling frameworks that reveal the latent structure of movement. My work spans trajectory map matching, hierarchical trajectory decomposition, cross-network projection between heterogeneous transportation systems, and behavior-aware mobility analytics. These methods aim to transform noisy mobility data into theoretically grounded, scalable, and interpretable models that support downstream tasks such as accessibility measurement, equity analysis, and system planning.

Broadly, I am interested in building the methodological foundations of mobility data science — developing tools, theories, and representations that make large-scale human movement data computationally reliable and scientifically meaningful. I am always happy to discuss research ideas and collaborations. 😄 🚀 ✨

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) . 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!