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Dr Jing Tang

Senior Lecturer

Department: Newcastle Business School

Dr. Jing Tang received her PhD in Computational Intelligence from Nanyang Technological University (NTU), Singapore. She previously worked as a research fellow in the Intelligent System Centre at NTU, and then as a Business Intelligence Consultant in a world-leading wind power company (Vestas) where she conducted data modelling, management, analysis and visualization in a large scale of practical settings. She worked as Senior Lecturer in Teesside University before she joined Northumbria University in 2020. Her teaching portfolio includes undergraduate and graduate level courses/modules related to Business Analytics, Machine Learning, Data Management and Visualization, and Decision Making. Her research interests lie in Business Analytics, Artificial Intelligence, Data Analytics, Decision Making, Optimization and Heuristic Algorithms, Social Networks Analysis and Recommender Systems.  

Jing Tang

Research Themes and Scholarly Interests

Dr. Jing Tang received her PhD in Computational Intelligence from Nanyang Technological University (NTU), Singapore. She previously worked as a research fellow in the Intelligent System Centre at NTU, and then as a Business Intelligence Consultant in a world-leading wind power company (Vestas) where she conducted data modelling, management, analysis and visualization in a large scale of practical settings. She worked as Senior Lecturer in Teesside University before she joined Northumbria University in 2020. Her teaching portfolio includes undergraduate and graduate level courses/modules related to Business Analytics, Machine Learning, Data Management and Visualization, and Decision Making. Her research interests lie in Business Analytics, Artificial Intelligence, Data Analytics, Decision Making, Optimization and Heuristic Algorithms, Social Networks Analysis and Recommender Systems.  

Key Publications

  • Please visit the Pure Research Information Portal for further information
  • Behavioral model summarisation for other agents under uncertainty, Pan, Y., Ma, B., Tang, J., Zeng, Y. 20 Sep 2021, In: Information Sciences
  • Evolutionary Multiagent Transfer Learning With Model-Based Opponent Behavior Prediction, Hou, Y., Ong, Y., Tang, J., Zeng, Y. Oct 2021, In: IEEE Transactions on Systems, Man and Cybernetics: Systems
  • Exploiting relational tag expansion for dynamic user profile in a tag-aware ranking recommender system, Pan, Y., Huo, Y., Tang, J., Zeng, Y., Chen, B. 4 Feb 2021, In: Information Sciences
  • Privacy-preserving Point-of-Interest Recommendation Based on Geographical and Social Influence, Huo, Y., Chen, B., Tang, J., Zeng, Y. 8 Jan 2021, In: Information Sciences
  • Tensor optimization with group lasso for multi-agent predictive state representation, Ma, B., Tang, J., Chen, B., Pan, Y., Zeng, Y. 7 Jun 2021, In: Knowledge-Based Systems
  • Toward data-driven solutions to interactive dynamic influence diagrams, Pan, Y., Tang, J., Ma, B., Zeng, Y., Ming, Z. 1 Sep 2021, In: Knowledge and Information Systems
  • Learning a Planning Domain Model from Natural Language Process Manuals, Huo, Y., Tang, J., Pan, Y., Zeng, Y., Cao, L. 17 Aug 2020, In: IEEE Access
  • Self-Improving Generative Adversarial Reinforcement Learning, Liu, Y., Zeng, Y., Chen, Y., Tang, J., Pan, Y. 8 May 2019, AAMAS 2019, Richland, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
  • A Group-based Approach to Improve Multifactorial Evolutionary Algorithm, Tang, J., Chen, Y., Deng, Z., Xiang, Y., Joy, C. 19 Jul 2018, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, Stockholm
  • An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations, Wan, S., Wang, F., Xu, G., Dong, J., Tang, J. Sep 2017, In: Fuzzy Optimization and Decision Making

Qualifications

Philosophy PhD May 05 2008


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