James Jianqiao Yu
余剑峤
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Professor

School of Computer Science and Technology

Harbin Institute of Technology, Shenzhen

University Town of Shenzhen, Nanshan District, Shenzhen, Guangdong, China

jqyu(at)hit.edu.cn jqyu(at)ieee.org Google Scholar
Hello!

I am Jianqiao, a full Professor at the School of Computer Science and Technology of Harbin Institute of Technology, Shenzhen. I received my B.Eng. and Ph.D. from The University of Hong Kong in 2011 and 2015.

I am passionate on innovating artificial intelligence techniques and using them for spatial-temporal data mining, large and foundation models. I have published more than 100 papers with 6000+ Google Scholar citations. I am one of the World’s Top 2% Scientists by Stanford University.

My current research interest focuses on 1) spatial-temporal data mining, 2) multi-modal large model, and 3) forecasting and logistics of future transportation. I am currently working on multi-modal large language models fusing spatial-temporal data with common modalities.

I was born in 1990 in Liaoning, China. I live with my wife and two cats 🐈小宝 & 🐈小葵. Dog in my portrait above is my “sister-in-law” 🐕小花. In my spare time, I like coding. I am the author of LaTeX Workshop, serving more than 3,600,000 academic writers.

I am looking for post-doctoral researchers to work with me on exciting AI and data mining topics. If you are interested, please send me an email with your vitae. Unfortunately, I am not taking non-local postgraduates at the moment.

Short Bio

James Jianqiao Yu is a Professor with the School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen. He received the B.Eng. and Ph.D. degree in Electrical and Electronic Engineering from the University of Hong Kong, Pokfulam, Hong Kong, in 2011 and 2015, respectively. He was a post-doctoral fellow at the University of Hong Kong from 2015 to 2018. He held professorship/lectureship at Southern University of Science and Technology, China and University of York, United Kingdom from 2018 to 2024. His general research interests are in data mining, large language models, intelligent transportation, and embodied artificial intelligence. His work is now mainly on spatial-temporal data mining, multi-modal foundation model, and forecasting and logistics of future transportation. He has published over 100 academic papers in top international journals and conferences, and representative papers have been selected as ESI highly cited papers. He was the World’s Top 2% Scientists since 2020 and of career by Stanford University. He is an Editor of the IEEE Transactions on Intelligent Transportation Systems and IET Smart Cities. He is a Senior Member of IEEE.

Selected Recent Publications [Full List]
  • CLEAR: Spatial-temporal Traffic Data Representation Learning for Traffic Prediction 📄 📚
    James Jianqiao Yu, Xinwei Fang, Shiyao Zhang*, and Yuxin Ma*
    IEEE Transactions on Knowledge and Data Engineering, in press, 2025
  • Scalable and Sustainable Graph-based Traffic Prediction with Adaptive Deep Learning 📄 📚
    James Jianqiao Yu
    IEEE Transactions on Knowledge and Data Engineering, Volume 36, Issue 11, 2024, Pages 6949--6961
  • ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model 📄 📚
    Yuanshao Zhu, James Jianqiao Yu*, Xiangyu Zhao*, Qidong Liu, Yongchao Ye, Wei Chen, Zijian Zhang, Xuetao Wei, and Yuxuan Liang*
    Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, August 2024, Pages 4676--4687
  • Citywide Estimation of Travel Time Distributions with Bayesian Deep Graph Learning 📄 📚
    James J.Q. Yu
    IEEE Transactions on Knowledge and Data Engineering, Volume 35, Issue 3, March 2023, Pages 2366--2378
  • Graph Construction for Traffic Prediction: A Data-driven Approach 📄 📚
    James J.Q. Yu
    IEEE Transactions on Intelligent Transportation Systems, Volume 23, Issue 9, September 2022, Pages 15015--15027
Representative Honors
  • World's Top 2% Scientists of Career, 2023, 2024
  • World's Top 2% Scientists of Single Year, 2020, 2021, 2022, 2023, 2024
  • Overseas High-Caliber Personnel Level-C, Shenzhen, 2019
Teaching University of York
  • Intelligent Systems: Machine Learning and Optimisation: S'24
Southern University of Science and Technology The University of Hong Kong
  • Embedded System: F'17, F'16
  • Engineering Management and Society: F'14