• Assistant Professor (2024/08~present)
  Data Science and Analytics Thrust and Internet of Things Thrust
  Information Hub
  Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
  
  

• Postdoc (2022/08~2024/08)
  Electrical and Computer Engineering
  Northwestern University, Evanston, USA
  Advisor: Prof. Randall Berry (IEEE Fellow) and Prof. Ermin Wei
  
  

• Ph.D. (2018/08~2022/07)
  Information Engineering
  The Chinese University of Hong Kong, Hong Kong SAR, China
  Advisor: Prof. Jianwei Huang (IEEE Fellow)
  
  

• B.Eng. (2014/08~2018/07)
  Information Science and Engineering
  Southeast University, Nanjing, China
  GPA:3.93/4.0, Ranking: 2/235
  
  
  

• Artificial intelligence: federated learning, machine unlearning, multi-agent coordination and game
• Network system: Internet of Things (IoT)
• Network economics: data trading, mechanism design

• Y. Cui, N. Ding^*, and M. Cheung, "AoI-aware Federated Unlearning for Streaming Data with Online Client Selection and Pricing," IEEE International Conference on Computer Communications (INFOCOM), 2025. (Acceptance rate 18.7%, CCF A)
• J. Cheng, N. Ding, J. C.S. Lui, and J. Huang, "OSTOR: Online Scheduling Framework for Trading Continuous Queries," IEEE International Conference on Data Engineering (ICDE), 2025. (CCF A)
• N. Ding, L. Gao, and J. Huang, "Incentive Mechanism Design for Federated Learning with Dynamic Network Pricing," IEEE Transactions on Mobile Computing (TMC), 2025. (CCF A)
• J. Cheng, N. Ding, J. C.S. Lui, and J. Huang, "Continuous Query-based Data Trading," ACM SIGMETRICS, 2024. (Acceptance rate 10%, CCF B)
• N. Ding, E. Wei, and R. Berry, "Strategic Data Revocation in Federated Unlearning," IEEE International Conference on Computer Communications (INFOCOM), 2024. (Acceptance rate 19.6%, CCF A)
• N. Ding, Z. Sun, E. Wei, and R. Berry, "Incentive Mechanism Design for Federated Learning and Unlearning," ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc), 2023. (Acceptance rate 21.9%, CCF B)
• N. Ding, L. Gao, and J. Huang, "Joint Participation Incentive and Network Pricing Design for Federated Learning," IEEE International Conference on Computer Communications (INFOCOM), 2023. (Acceptance rate 19.2%, CCF A)
• N. Ding, L. Gao, and J. Huang, "Optimal Pricing Design for Coordinated and Uncoordinated IoT Networks," IEEE Transactions on Mobile Computing (TMC), 2022. (CCF A)
• N. Ding, L. Gao, J. Huang, Xin Li, and Xin Chen, "Optimal Pricing Under Vertical and Horizontal Interaction Structures for IoT Networks," IEEE International Conference on Computer Communications (INFOCOM), 2022. (Acceptance rate 19.9%, CCF A, collaborated with Huawei)
• N. Ding, Z. Fang, L. Duan, and J. Huang, "Optimal Incentive and Load Design for Distributed Coded Machine Learning," IEEE Journal on Selected Areas in Communications (JSAC), vol. 39, no. 7, pp. 2090-2104, Jul. 2021. (CCF A)
• N. Ding, Z. Fang, and J. Huang, "Optimal Contract Design for Efficient Federated Learning With Multi-Dimensional Private Information," IEEE Journal on Selected Areas in Communications (JSAC), vol. 39, no. 1, pp. 186-200, Jan. 2021. (CCF A)
• N. Ding, Z. Fang, L. Duan, and J. Huang, "Incentive Mechanism Design for Distributed Coded Machine Learning," IEEE International Conference on Computer Communications (INFOCOM), 2021. (Acceptance rate 19.9%, CCF A)
• N. Ding, Z. Fang, and J. Huang, "Information Disclosure Game on Sharing Platforms," IEEE Global Communications Conference (GLOBECOM), 2020.
• N. Ding, Z. Fang, and J. Huang, "Incentive Mechanism Design for Federated Learning with Multi-Dimensional Private Information," International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2020.

PhD Students:

Organizing/Technical Committee:

Technical Review: