Brief Bio

Xiuwen Yi (易修文) is currently a Researcher & Data Scientist at JD Tech . He got his Ph.D. degree in Computer Science and Technology from Southwest Jiaotong University in 2018. He was a Postdoctoral Researcher at Tsinghua University during 2019-2020, a visiting scholar at Penn State University during 2017-2018, and a research intern at Microsoft Research Asia during 2014-2017. His research interests include Data Intelligence, Knowledge Discovery, Deep Learning, and Urban Computing. He serves as Associate Editor of IET Smart Cities journal. He has published 20+ referred publications at prestigious international conferences and journals (with 2,000+ citations). Also, he is experienced in building real-world AI applications, consisting of UrbanAir, CityTraffic, GasTheft, SmartHeat, EventCommand and ScenicBrain. He was selected into the Beijing Nova Program (2021).


Ph.D. in Computer Science and Technology, Southwest Jiaotong University, 2013 – 2018

Supervised by Prof. Tianrui Li & Prof. Yu Zheng

B.S. in Software Engineering, Southwest Jiaotong University, 2009 – 2013

Mao Yisheng Honors Class

Work Experiences

  • Researcher & Data Scientist, JD Tech, 2018 - Present
  • Postdoctoral Researcher, Tsinghua University, 2019 - 2020, advised by Prof. Jie Tang
  • Visiting Scholar, Pennsylvania State University, 2017 - 2018, advised by Prof. Zhenhui Li
  • Research Intern, Urban Computing Group @ Microsoft Research Asia, 2014 – 2017
  • Development Intern, Operation Excellence Group @ Intel, 2012 – 2013
  • Selected Publications

    Real Systems


  • Filling missing values of geo-sensory time series data
  • Inferring fine-grained air quality of arbitrary location
  • Forecasting station-level and city-level air quality over the next 7 days
  • Study the correlation between vehicular emissions and air pollutions
  • UrbanAir system has been deployed with the Ministry of Environmental Protection of China, where the prediction accuracy have 22% improvements comparing with the official predictions from Beijing municipal environmental monitoring center


  • Inferring city-wide traffic speed and volume conditions over the whole road network
  • Managing massive trajectories on the cloud (Azure)
  • Predicting citywide crowd flow for both regular and irregular regions
  • CityTraffic system has been deployed with the big data demonstration center in Guiyang, providing real-time city-wide traffic speed and volume information. The system is implemented with a parallel big data modeling architecture


  • Detecting gas-theft suspects with gas consumption and transition data
  • Predicting daily/monthly gas usage of different end-users
  • Diagnosing fault errors of gas regulator for predictive maintenance
  • GasTheft system has been deployed with the Beijing Gas Group Company, detecting suspects of gas-theft using data-driven approaches for reducing the quantity difference between supply and marketing


  • Predicting indoor temperature for constructing data-driven environmental simulator
  • Optimizing temperature in heat exchange station for improving indoor comfort
  • Scheduling Building HVAC Using Deep Reinforcement Learning
  • SmartHeating system has been deployed with the Tianjin Energy Investment Company and hotels, optimizing cold and hot supply for saving energy

    Academic Services

    Associate Editor

  • IET Smart Cities, 2020 - Present
  • Program Committee Member

  • 2020: KDD、IJCAI; 2021: KDD、IJCAI、CIKM; 2022: KDD、AAAI、SDM
  • Journal Reviewer

  • TKDE、TIST、TKDD、TBD、Information Fusion、Neural Networks、Knowledge-Based Systems、IEEE Systems Journal