My research focuses on three directions: (1) AI Agents and Foundation Models (agentic systems, recursive self-improvement, and multimodal reasoning); (2) Intelligent Transportation and Autonomous Systems (spatiotemporal learning and autonomous driving); and (3) Trustworthy AI (uncertainty quantification, reliability and calibration, and fairness).
Our paper TopoRefine is under review at NeurIPS 2026, introducing plug-and-play discrete graph refinement for autonomous-driving topology reasoning.
Aug
2026
Released EarthVerse, a benchmark for evaluating scientific agents across dynamic Earth systems and natural hazards.
Jun
2026
Released our uncertainty-aware study of public-transit gains and spatially uneven demand changes after NYC congestion pricing.
May
2026
Paper AlphaOPT accepted at KDD 2026; also released Bridge for retrieval-augmented urban demand forecasting.
Apr
2026
Released Ozone, a unified platform for reproducible transportation research.
Apr
2026
Successfully defended my Ph.D. thesis at MIT. I am grateful to my advisor, Prof. Jinhua Zhao, and my committee.
Mar
2026
Released RiskMV-DPO for risk-controllable multi-view driving-scenario generation.
Jan
2026
TrustEnergy appeared at AAAI 2026 (AI for Social Impact, Oral).
Jun
2025
Paper "Human-guided Urban Form Generation Using Multimodal Diffusion Models" accepted at Building and Environment.
May
2025
Paper "Sparkle: Mastering Basic Spatial Capabilities in Vision Language Models" accepted at EMNLP 2025 (Findings).
Aug
2025
Paper "Sparkle: Mastering Basic Spatial Capabilities in Vision Language Models Elicits Generalization to Composite Spatial Reasoning" accepted at IJCAI MKLM Workshop as
Best Paper Award.
Jun
2025
Paper "Dynamic autoregressive tensor factorization for pattern discovery of spatiotemporal systems" accepted at
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
Jun
2025
Paper "Towards Foundation Model for Spatiotemporal Data Analysis" accepted at SSTD 2025 (International Symposium on Spatial and Temporal Data).
Mar
2025
Our paper "Mitigating Spatial Disparity in Urban Prediction Using Residual-Aware Spatiotemporal Graph Neural Networks" has received Best Paper Award at WWW WebsST workshop2025.
Mar
2025
Paper "Reliable lmputation of Incomplete Crash Data for Predicting Driver injury Severity" accepted at
Accident Analysis & Prevention (AAP).
Feb
2025
Paper "GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks" accepted at
ICLR 2025 (Spotlight).
Feb
2025
Paper "Time Series Supplier Allocation via Deep Black-Litterman Model" accepted at
AAAI 2025 (Oral).
Feb
2025
Paper "Mitigating Spatial Disparity in Urban Prediction Using Residual-Aware Spatiotemporal Graph Neural Networks" accepted at
WWW 2025 and also appearing in
TRB 2025.
Nov
2024
Paper "ItiNera: Integrating Spatial Optimization with Large Language Models for Open-domain Urban Itinerary Planning" accepted at
EMNLP 2024 (Industry Track), also
KDD UrbComp 2024 Best Paper.
Oct
2024
Presented "Quantifying Uncertainty: Advancing Robustness, Reliability, and Fairness in AI-Driven Transportation Demand Modeling"
at INFORMS 2024.
Aug
2024
Paper "Uncertainty-aware Probabilistic Graph Neural Networks for Road-level Traffic Crash Prediction" accepted at
Accident Analysis & Prevention (AAP) 2024.
Jun
2024
Presented "Uncertainty Quantification on Sparse Spatiotemporal Data Prediction"
at Machine Learning Seminar, Morgan Stanley.
Jun
2024
Started my internship at Morgan Stanley advised by Majid Behbahani
Mar
2024
Paper "SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks" accepted at
SIGSPATIAL 2024 (Oral),
also Spotlight talk at TGL Workshop, NeurIPS 2023.
Oct
2023
Paper "Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction" accepted at
CIKM 2023.
Oct
2023
Presented "Modeling Multi-perspective Nature of Urban Dynamics"
at the Allen Turing Institute.
Oct
2023
Presented "Modeling Multi-perspective Nature of Urban Dynamics"
at The Space Time Lab, University College London.
Oct
2023
Presented "Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks"
at The Bartlett Centre for Advanced Spatial Analysis, UCL.
Jul
2023
Presented "Uncertainty Quantification of Sparse Trip Demand Prediction"
at Lyft.
Jul
2023
Presented "Deep Hybrid Model with Urban Road Network for Travel Demand Analysis"
at the Transit Data Section, WCTR 2023.
May
2023
Presented "Deep Hybrid Model with Urban Road Network"
at the MIT Mobility Initiative Forum.
Apr
2023
Presented "Uncertainty Quantification of Sparse Trip Demand Prediction"
at the Urban Artificial Intelligence Laboratory, University of Florida.
Feb
2023
Presented "Deep Hybrid Model with Urban Road Network for Travel Demand Analysis"
at CEE Research Days, MIT Media Lab.
Oct
2022
Presented "Uncertainty Quantification of Sparse Trip Demand Prediction"
at the College of Computer Science, Sichuan University.
Aug
2022
Paper "Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks" accepted at
KDD 2022 (Oral).
ACM International Conference on Advances in Geographic Information Systems 2024Oral presentation Also at Temporal Graph Learning Workshop @ NeurIPS2023Spotlight talk arXiv |
code |
slideslive |
Graduate Excellence Fellowship, McGill University (2019 & 2021)
Hsue-shen Tsien Class, Shanghai Jiao Tong University (2019)
Chungtsung Scholarship, Hui-Chun Chin and Tsung-Dao Lee Chinese Undergraduate Research Endowment (2017)
First Prize (1/135), Chinese Big Data Innovation Application and Modeling Contest (2017)
Eleme Scholarship, Shanghai Jiao Tong University (2016 & 2017)
Excellent Student, Shanghai Jiao Tong University (2016)
Service
Conference Reviewer
ICLR, TRB, IEEE ITSC
Journal Reviewer
IEEE T-IST, IEEE IoT, IET ITS, JCGS, IEEE TNNLs, TR-Part C, Journal of Cleaner Production, Neurocomputing, TGEI, TGSI, International Journal of Digital Earth, Geocarto International, Geo-spatial Information Science, Transportation Research Record
Jinghan Xu (KTH Royal Institute of Technology, 2026) Zeyuan Niu (Shanghai Jiao Tong University, 2025) Yifeng Liu (MIT, 2024) Yunlin Li (University of Oxford, 2025) Chonghe Jiang (Chinese University of Hong Kong, 2024 → Ph.D. at MIT) Yihong Tang (University of Hong Kong, 2024 → Ph.D. at McGill University) Zepu Wang (UPenn, 2023 → Ph.D. at University of Washington)
Undergraduate Students
Zhiqing Cui (Nanjing University of Information Science and Technology, 2026)
Chenshuo Li (Sichuan University, 2025)
Xiaoyang Cao (Tsinghua University, 2024 → Ph.D. at MIT) Xiaoyu Yan (Zhejiang University, 2023 → Ph.D. at Northwestern University) Peisen Li (Tsinghua University, 2023 → Ph.D. at University of Michigan)
