Jie Feng is currently a postdoctoral researcher in the Department of Electronic Engineering at Tsinghua University. From 2021 to 2023, he worked at Meituan as a researcher specializing in intelligent decision-making and large language models. He received his B.S. and Ph.D. degrees (advised by Prof. Yong Li) in electronic engineering from Tsinghua University in 2016 and 2021, respectively. His research mainly focuses on spatial intelligence, multi-modal large language models, human behavior modeling, urban science and spatiotemporal data mining, with over 40 papers published in top-tier venues including KDD, ACL, ICCV, WWW, NAACL, AAAI, UbiComp, TKDE, etc. His work has garnered more than 3500 citations on Google Scholar. His research is supported by the Shuimu Tsinghua Scholar Program.

We are seeking self-motivated interns and collaborators to conduct research on spatio-temporal data mining, large language models, embodied agent, etc., with us remotely or at Tsinghua. Our interns have good record of publishing first-author papers in CCF-A conferences/journals. I also have strong connections with the industry (e.g., Meituan, Tencent) and can recommend good opportunities for internships or full-time positions. Feel free to contact me via email if you are interested.

Research Interests

1. Spatial Intelligence with Multi-modal Large Language Models in Open World, e.g., CityGPT-KDD2025, CityBench-KDD2025, UrbanLLaVA-ICCV2025.
2. Building Intelligent Agents with Large Language Models for Real-world Applications, e.g., AgentMove-NAACL2025, PIGEON-ACL2025, TrajAgent, LMP.
3. Spatiotemporal Data Mining: trajectory mining, traffic forecasting, e.g., DeepMove-WWW2018, MoveSim-KDD2020, DeepSTN+-AAAI2019, UniST-KDD2024, High Efficiency Delivery Network-KDD2024.
4. Urban Science: human dynamics, urban dynamics, in-depth and data-driven analyses of urban issues.

Survey

1. Lin Chen, Yunke Zhang, Jie Feng, et al. “AI Agent Behavioral Science.” preprint 2025.06.
2. Jie Feng, Jinwei Zeng, et al. “A Survey of Large Language Model-Powered Spatial Intelligence Across Scales: Advances in Embodied Agents, Smart Cities, and Earth Science.” preprint 2025.04. Chinese article by Zhuanzhi.
3. Fengli Xu, Qianyue Hao, et al. “Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models.” preprint 2025.01.
4. Fengli Xu, Jun Zhang, Chen Gao, Jie Feng, Yong Li. “Urban Generative Intelligence (UGI): A foundational platform for agents in embodied city environment.” preprint 2023.12
5. Jingtao Ding, Yunke Zhang, et al. “Understanding World or Predicting Future? A Comprehensive Survey of World Models.” ACM Computing Surveys 2025
6. Fuxian Li, Jie Feng, et al. “Dynamic graph convolutional recurrent network for traffic prediction: Benchmark and solution.” ACM TKDD 2023

Talks

1. “LLM-Powered Spatial Intelligence Across Scales: Advances in Embodied Agents, Smart Cities, and Earth Science”, Tutorial, ACM SIGSPATIAL CHINA Saptial Data Intelligence 2025 Conference, Xiamen
2. “LLM-Based Agentic Framework: A Novel Paradigm for Modeling Human Mobility”, Invited Talk, ACM SIGSPATIAL CHINA Saptial Data Intelligence 2025 Conference, Xiamen
3. “CityGPT: From LLM to Urban Generative Intelligence”, Invited Talk, CCF ChinaData 2024 Conference, Boao

News

• New![2025.06] Our survey on world models has been published in ACM Computing Surveys. We welcome any discussion and collaboration!
• New![2025.06] Our paper UrbanLLaVA has been accepted by ICCV 2025!
• New![2025.06] I am honored to have been selected as an Excellent Reviewer for KDD 2025.
• New![2025.05] Three papers have been accepted by KDD 2025, including CityGPT, CityBench and LocalEval!
• New![2025.05] Two papers have been accepted by ACL 2025, including Benchmarking Basic Spatial Abilities and PIGEON!
• New![2025.04] I am glad to be selected as one of 2025 Spatial Data Intelligence Rising Star! news.
• New![2025.01] AgentMove has been accepted as a main conference paper at NAACL 2025, and the code has been released. Feel free to try it out!
• [2024.12] The datasets and implementation codes for CityGPT and CityBench projects are now open-source. Welcome any suggestions and collaboration!
• [2024.10] We released a preprint paper about urban simulation platform with massive LLM-based agents, opencity.
• [2024.10] I am glad to be selected as one of Stanford/Elsevier Top 2% Scientists 2024.
• [2024.05] Two papers have been accepted in KDD 2024! High Efficiency Delivery Network and UniST.
• [2023.12] We released a preprint paper about the Urban Generative Intelligence (UGI) in the era of large language models. For more details, please refer to arxiv.
• [2023.04] Meituan’s Real-Time Intelligent Dispatching Algorithms wins the INFORMS 2023 Edelman Finalist Reward. I am glad to contribute to the part “Divide-and-Conquer” framework, the algorithm details about this is introduced in the High Efficiency Delivery Network.

Selected Publications

* Equal contribution; # Correspondence; † Intern contributor

Spatial Intelligence with Large Language Models

1. UrbanLLaVA: A Multi-modal Large Language Model for Urban Intelligence
   Jie Feng, Shengyuan Wang, Tianhui Liu, Yanxin Xi, Yong Li
   ICCV 2025 (CCF A) Codes PDF
2. CityGPT: Empowering Urban Spatial Cognition of Large Language Models
   Jie Feng*, Tianhui Liu*, Yuwei Du, Siqi Guo, Yuming Lin, Yong Li
   KDD 2025 Research (CCF A) Codes PDF
3. CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks
   Jie Feng*, Jun Zhang*, Tianhui Liu*, Xin Zhang, Tianjian Ouyang, Junbo Yan, Yuwei Du, Siqi Guo, Yong Li
   KDD 2025 D&B (CCF A) Codes PDF

Human Behavior Analytics and Modeling

1. AgentMove: A Large Language Model based Agentic Framework for Zero-shot Next Location Prediction
   Jie Feng, Yuwei Du, Jie Zhao, Yong Li
   NAACL 2025 Main (CCF B) Codes PDF
2. Open-Set Living Need Prediction with Large Language Models
   Xiaochogn Lan, Jie Feng#, Yizhou Sun, Chen Gao, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Yong Li#
   ACL 2025 Findings (CCF A) Codes PDF
3. DeepMove: Predicting Human Mobility with Atentional Recurrent Networks
   Jie Feng, Yong Li, Chao Zhang, Funing Sun, Fanchao Meng, Ang Guo, Depeng Jin.
   WWW 2018 (CCF A) Codes(star 151) | PDF | Link | #5 Most Influential Paper in WWW 2018

AI-Driven Decision-Making

1. Meituan’s Real-Time Intelligent Dispatching Algorithms Build the World’s Largest Minute-Level Delivery Network
   Yile Liang, Haocheng Luo, Haining Duan, Donghui Li, Hongsen Liao, Jie Feng, Jiuxia Zhao, Hao Ren, Xuetao Ding, Ying Cha, Qingte Zhou, Chenqi Situ, Jinghua Hao, Ke Xing, Feifan Yin, Renqing He, Yang Sun, Yueqiang Zheng, Yipeng Feng, Zhizhao Sun, Jingfang Chen, Jie Zheng, Ling Wang
   INFORMS 2023 Link | Edelman Finalist Reward | PDF
2. Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments
   Yile Liang, Jiuxia Zhao, Donghui Li, Jie Feng#, Chen Zhang, Xuetao Ding, Jinghua Hao, Renqing He
   KDD 2024 ADS (CCF A) PDF Link

Spatiotemporal Time Series Modeling

1. UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction
   Yuan Yuan, Jingtao Ding, Jie Feng, Depeng Jin, Yong Li
   KDD 2024 Research (CCF A) Codes(star 180) | PDF | Link | #5 Most Influential Paper at KDD 2024
2. DeepSTN+: Context-aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis
   Ziqian Lin*, Jie Feng*, Ziyang Lu, Yong Li, Depeng Jin
   AAAI 2019 (CCF A) Codes(star 66) PDF Link
3. Dynamic graph convolutional recurrent network for traffic prediction: benchmark and solution
   Fuxian Li, Jie Feng, Huan Yan, Guangyin Jin, Fan Yang, Funing Sun, Depeng Jin, Yong Li
   TKDD 2023 (CCF B) Codes(star 296) | PDF | Link | #1 Most Cited Paper in TKDD 2023