Academic Profile : Faculty

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Prof Zhang Jie
Professor, School of Computer Science and Engineering
External Links
Jie Zhang is a Professor of the School of Computer Science and Engineering at NTU Singapore, leading the Computational Intelligence Group. He obtained Ph.D. in Cheriton School of Computer Science from University of Waterloo and was the recipient of Alumni Gold Medal in 2009. Then he joined NTU as an Assistant Professor and was promoted to Associate Professor in 2015. From 2017-2018, he was appointed as Tan Chin Tuan Exchange Fellowship, New York University. He was also an Adjunct Fellow, Singapore Institute of Manufacturing Technology (SIMTech), A*STAR, from 2020-2021. His papers have been published by top journals and conferences and won several best paper awards. Jie Zhang is also active in serving research communities.
Jie Zhang's research work is in the area of User Modeling, one of the important subareas of Artificial Intelligence. It has been focused on providing personalized recommendations to users on which others to interact with (e.g., do business with or acquire information from), by modeling: 1) the trust (i.e., reliability, capability and honesty) of the others; and 2) the preferences of the users. Dr. Zhang has made significant contributions to both trust modeling and preference modeling. More interestingly, for accurately modeling trust, he has specifically taken good care of user preference (subjectivity); for accurately modeling preference, he has well leveraged the trust relationships between users.

+ Artificial Intelligence
+ Machine Learning
+ User Modeling
+ Trust and Preference
  • A Simulation and Policy Evaluation Toolset for Smart Urban Mobility Systems with Emerging Technologies
  • Artificial Intelligence for Quantitative Trading
  • Design of advance machine learning and deep learning algorithm for pattern recognition
  • Distributed Smart Value Chain (DSVC)
  • Never-Ending Deep Learning Agent for Non-stationary Data Streams
  • Parking Supply Planning In Future Mobility System With Autonomous Vehicles
  • Physics and Knowledge Transfer-based Cognitive Digital Twin for Advanced Battery Analytics
  • Virality Modelling and Analysis of Firm-specific Information on Social Media
  • WP2: Cognitive Digital Twin and Physics-based ML for Battery Analytics and WP3: Edge Intelligence for Low Cost and Deployable Solutions (PI: Wen Yonggang)