Jun Huang

Jun Huang

Ph.D., Assistant Professor, EECS Department, South Dakota State University

Research Interest

Networking for (Trustworthy) AI
Distributed Learning in Mobile Systems
Cyber-Physical System

About me

Jun Huang (M’12-SM’16) received a Ph.D. degree (with honors) from the Institute of Network Technology, Beijing University of Posts and Telecommunications, China, in 2012. He is now an Assistant Professor in the Department of Electrical Engineering and Computer Science (EECS) at South Dakota State University, where he directs the Wireless Autonomy and Intelligent Control (WAIC) Laboratory. Before that, he was a Non-tenure track faculty member at Baylor University. He held a professor appointment at Northwestern Polytechnical University and Chongqing University of Posts and Telecommunications in China from 2015 to 2021.

Dr. Huang was a Visiting Scholar at the University of British Columbia, a Research Fellow at the South Dakota School of Mines & Technology and the University of Texas at Dallas, and a Guest Professor at the National Institute of Standards and Technology. He was the recipient of the Best Paper Award from IEEE IPCCC in 2025 and EAI Mobimedia in 2019, the Outstanding Service Award from ACM RACS in 2017, 2018, and 2019, and the Outstanding Research Award (Tier I) from CQUPT in 2019. He is the Technical Editor of ACM SIGAPP Applied Computing Review and an Associate Editor of IEEE Communications Surveys and Tutorials, IEEE Network, IEEE Internet of Things Journal, Digital Communications and Networks, IET Wireless Sensor Systems, and ICT Express. He guest-edited several special issues in IEEE/ACM journals. He also chaired and co-chaired multiple conferences in communications and networking, and organized numerous workshops at major IEEE and ACM events. He is a Senior Member of the IEEE.

News

  • Paper Accepted

    Two papers, “Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memory” and “FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning,” have been accepted for publication in the proceedings of the 45th IEEE International Performance Computing and Communications Conference (IPCCC 2026) (AR: 23.9%).

  • Paper Accepted

    Our paper, “Exposing and Resolving Spurious Isolation in Federated Multimodal Continual Learning,” has been accepted for publication in IEEE Transactions on Multimedia.

  • Paper Accepted

    Our paper, “RELIEF: Turning Missing Modalities into Training Acceleration for Federated Learning on Heterogeneous IoT Edge,” has been accepted for publication in IEEE Internet of Things Journal.

  • Paper Accepted

    Our paper, “BR-FiLM: Bounded Residual Channel-Quality Conditioning for Automatic Modulation Recognition,” has been accepted for publication in the Proceedings of IEEE MILCOM 2026.

  • Editor Appointment

    Dr. Huang has been invited to join the editorial board of the IEEE Communications Surveys and Tutorials (IF: 50.6).

  • Faculty Spotlight

    https://www.sdstate.edu/news/2026/08/huang-uses-machine-unlearning-make-ai-trustworthy

  • Paper Accepted

    Our paper, “Transmission Games in RIS-Aided MIMO Interference Channels with Nonlinear Energy Harvesting,” has been accepted for publication in IEEE Transactions on Wireless Communications.

  • Paper Accepted

    Our paper, “Toward Trustworthy Federated Unlearning for Mobile Autonomous Systems,” has been accepted for publication in IEEE Network.

  • Editor Appointment

    Dr. Huang has been invited to join the editorial board of the IEEE Network.

  • Paper Accepted

    Our paper, Combating Knowledge Diversity and Catastrophic Forgetting in UAV-Assisted Collaborative Vehicular Learning: A Game-Theoretic Approach, has been accepted for publication in ACM Transactions on Autonomous and Adaptive Systems.

  • SD Competitive Research Grant

    My Competitive Research Grant (CRG) proposal has been selected for funding by the South Dakota Board of Regents.

  • Paper Accepted

    Our papers, “SCALE: Sensitivity-Aware Federated Unlearning with Information Freshness Optimization for Mobile Edge Computing” and “From Alpha to Omega: Lifecycle-Aware Forgetting Defense in Federated Continual Learning for Planetary Exploration” have been accepted by 46th IEEE International Conference on Distributed Computing Systems (ICDCS 2026) (AR: 18.59%).

  • TPC Invitation

    Dr. Huang has been invited to serve on the Technical Program Committee for IEEE INFOCOM 2027.

  • Editor Appointment

    Dr. Huang has been invited to join the editorial board of the IEEE Internet of Things Journal.

  • Editor Appointment

    Dr. Huang has been invited to join the editorial board of the IET Wireless Sensor Systems.

  • Paper Accepted

    Our paper, titled “Securing Smart Agriculture with Communication-Efficient Federated Unlearning,” has been accepted by IEEE HPSR 2026.

  • Paper Accepted

    Our paper, “X of Information” Continuum: A Survey on AI-Driven Multi-dimensional Metrics for Next-Generation Networked Systems, has been accepted for publication in IEEE Communications Surveys and Tutorials (IF: 46.7).

  • Paper Accepted

    Our paper, “A Review of Continual Learning in Edge AI,” has been accepted for publication in IEEE Transactions on Network Science and Engineering.

  • Paper Accepted

    Our paper, “A Stochastic Geometry-Based Analysis of SWIPT-Assisted Underlaid Device-to-Device Energy Harvesting,” has been accepted for publication in ACM SIGAPP Applied Computing Review.

  • Paper Accepted

    Our paper, “Transformer-Based Dynamic Resource Allocation for Multi-Carrier NOMA Systems,” has been accepted for publication in IEEE Transactions on Cognitive Communications and Networking.

  • Best Paper Award

    Our paper, “A Dual-Level Game-Theoretic Approach for Collaborative Learning in UAV-Assisted Heterogeneous Vehicle Networks,” won the Best Paper Award (1/34/147) at the 44th IEEE International Performance Computing and Communications Conference (IPCCC 2025).

  • Paper Accepted

    Our paper, titled “Learning to Defend: A Multi-Agent Reinforcement Learning Framework for Stackelberg Security Game in Mobile Edge Computing” has been accepted by IEEE ICNC 2026.

  • Paper Accepted

    Our paper, “Enhancing Vehicular Platooning with Wireless Federated Learning: A Resource-Aware Control Framework,” has been accepted for publication in the most prestigious journal IEEE/ACM Transactions on Networking.

  • Paper Accepted

    Our paper, “A Dual-Level Game-Theoretic Approach for Collaborative Learning in UAV-Assisted Heterogeneous Vehicle Networks,” has been accepted for publication in the proceedings of the 44th IEEE International Performance Computing and Communications Conference (IPCCC 2025).

  • Paper Accepted

    Our paper, “Real-time Intelligent Healthcare Enabled by Federated Digital Twins with AoI Optimization,” has been accepted for publication in IEEE Network.

  • News@Brookings Register

    Our work on machine learning in UAV communications featured in The Brookings Register (Link)!

  • Paper Accepted

    Our paper, “FedTD3: An Accelerated Learning Approach for UAV Trajectory Planning,” has been accepted by the International Conference on Wireless Artificial Intelligent Computing Systems and Applications (WASA) 2025.

  • NSF Panel

    Dr. Huang has been invited to serve as a panelist for the NSF.

  • Paper Accepted

    Our paper, “A Fast UAV Trajectory Planning Framework in RIS-assisted Communication Systems with Accelerated Learning via Multithreading and Federating,” has been accepted by IEEE Transactions on Mobile Computing.

  • Invited Talk


  • News@SDSU

    Why Is Federated Learning Important for 5G Networks?

  • Two Ph.D. Openings

    I am looking for two self-motivated Ph.D. students working on Federated Learning in Wireless Networking and Mobile Computing areas starting in Spring/Fall 2025. Two (Research/Teaching) Assistantships are available. Please email me your CV, Transcript, and Publication (if any). More information about the Ph.D. program in Computer Science at SDSU can be found here.

  • NSF Award

    I am grateful that my first NSF award has been granted. Many thanks to the generosity of the NSF!

  • Paper Accepted by COMST

    Our paper “Combining Federated Learning and Edge Computing toward Ubiquitous Intelligence in 6G Network: Challenges, Recent Advances, and Future Directions” has been accepted for publication in the IEEE Communications Surveys and Tutorials. (IF: 35.6)

  • ACM Journal on Autonomous Transportation Systems Special Issue on Federated Learning for Mobile Edge Computing-empowered Autonomous Vehicle Systems

    Call for Papers: special issue on Federated Learning for Mobile Edge Computing-empowered Autonomous Vehicle Systems, ACM Journal on Autonomous Transportation Systems.

Research Projects

Trustworthy Federated Unlearning for Mobile Autonomous Systems


Funding Source: SDBOR
Role: Sole PI
Total Budget: $90K
Duration: Jul 2026 – Aug 2027

CRII: NeTS: Resource Management for Mobile Terminal Collaboration with Incomplete Information: From Theory to Practice



Funding Source: NSF
Role: Sole PI
Total Budget: $175K
Award Number: 2348422
Duration: Oct 2024 – Sep 2026

Teaching

Selected Publications

Networking for Trustworthy AI

[1] Z. Ding and J. Huang, “Toward Trustworthy Federated Unlearning for Mobile Autonomous Systems,” IEEE Network, 2026, in print.

[2] Z. Ding, B. Wu, and J. Huang, “SCALE: Sensitivity-Aware Federated Unlearning with Information Freshness Optimization for Mobile Edge Computing,” in Proc. IEEE ICDCS 2026, Seoul, Korea, pp. 1476-1486, Jun. 2026.

Networking4AI

[1] B. Wu, Z. Ding, and J. Huang, “Exposing and Resolving Spurious Isolation in Federated Multimodal Continual Learning,” IEEE Transactions on Multimedia, 2026, in print.

[2] B. Wu, Z. Ding, and J. Huang, “RELIEF: Turning Missing Modalities into Training Acceleration for Federated Learning on Heterogeneous IoT Edge,” IEEE Internet of Things Journal, 2026, in print.

[3] Z. Ding, J. Huang, Y. Zhao, and Z. Cai, “Combating Knowledge Diversity and Catastrophic Forgetting in UAV-Assisted Collaborative Vehicular Learning: A Game-Theoretic Approach,” ACM Transactions on Autonomous and Adaptive Systems, 2026, in print.

[4] B. Wu, J. Huang, and Y. Zhao, “From Alpha to Omega: Lifecycle-Aware Forgetting Defense in Federated Continual Learning for Planetary Exploration,” in Proc. IEEE ICDCS 2026, Seoul, Korea, Jun. 2026.

[5] B. Wu, J. Huang, and S. Yu, “‘X of Information’ Continuum: A Survey on AI-Driven Multi-Dimensional Metrics for Next-Generation Networked Systems,” IEEE Communications Surveys & Tutorials, vol. 28, pp. 5307-5344, 2026.

AI4Networking

[1] B. Wu, Z. Ding, and J. Huang, “A Review of Continual Learning in Edge AI,” IEEE Transactions on Network Science and Engineering, vol. 13, pp. 6571-6588, 2026.

[2] L. Dong, J. Huang, and R. W. Heath, “Transformer-Based Dynamic Resource Allocation for Multi-Carrier NOMA Systems,” IEEE Transactions on Cognitive Communications and Networking, vol. 12, pp. 4926-4941, 2026.

[3] B. Wu, J. Huang, Q. Duan, L. Dong, and Z. Cai, “Enhancing Vehicular Platooning with Wireless Federated Learning: A Resource-Aware Control Framework,” IEEE Transactions on Networking, vol. 34, pp. 1479-1494, 2026.

[4] J. Huang, B. Wu, Q. Duan, L. Dong, and S. Yu, “A Fast UAV Trajectory Planning Framework in RIS-assisted Communication Systems with Accelerated Learning via Multithreading and Federating,” IEEE Transactions on Mobile Computing, vol. 24, no. 8, pp. 6870-6885, Aug. 2025.

[5] Q. Duan, J. Huang, S. Hu, R. Deng, Z. Lu, and S. Yu, “Combining Federated Learning and Edge Computing toward Ubiquitous Intelligence in 6G Network: Challenges, Recent Advances, and Future Directions,” IEEE Communications on Survey & Tutorial, vol. 25, no. 4, pp. 2892-2950, Fourthquarter 2023.

D2D and 5G Communications

[1] X. Xu, Q. Chen, H. Jiang and J. Huang, “Millimeter-Wave NR-U and WiGig Coexistence: Joint User Grouping, Beam Coordination, and Power Control,” IEEE Transactions on Wireless Communications, vol. 21, no. 4, pp. 2352-2367, April 2022.

[2] J. Huang, B. Yu, C. Xing, T. Cerny, and Z. Ning, “Online Energy Scheduling Policies in Energy Harvesting Enabled D2D Communications,’’ IEEE Transactions on Industrial Informatics, vol. 17, no. 8, pp. 5678-5687, Aug. 2021.

[3] J. Huang, C. Xing, and M. Guizani, “Power Allocation for D2D Communications With SWIPT,’’ IEEE Transactions on Wireless Communications, vol. 19, no. 4, pp. 2308-2320, Apr. 2020.

[4] J. Huang, Y. Zhou, Z. Ning, and H. Gharavi, “Wireless Power Transfer and Energy Harvesting: Current Status and Future Prospects,’’ IEEE Wireless Communications, vol. 26, no. 4, pp. 163-169, Aug. 2019.

[5] J. Huang, J. Zou, and C. Xing, “Energy-efficient Mode Selection for D2D Communications in Cellular Networks,’’ IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 4, pp. 869-882, Oct. 2018.

Internet of Vehicles and MEC

[1] Z. Ning, K. Zhang, X. Wang, L. Guo, X. Hu, J. Huang, B. Hu, and R. Y. K. Kwok, “Intelligent Edge Computing in Internet of Vehicles: A Joint Computation Offloading and Caching Solution,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 4, pp. 2212-2225, April 2021.

[2] J. Huang, M. Zhao, Y. Zhou, and C. Xing, “In-Vehicle Networking: Protocols, Challenges, and Solutions,’’ IEEE Network, vol. 33, no. 1, pp. 92-98, Jan./Feb. 2019.

[3] Z. Ning, P. Dong, X. Wang, L. Guo, J. Rodrigues, X. Kong, J. Huang, and R. Y. K. Kwok, “Deep Reinforcement Learning for Intelligent Internet of Vehicles: An Energy-Efficient Computational Offloading Scheme,” IEEE Transactions on Cognitive Communications and Networking, vol. 5, no. 4, pp. 1060-1072, Dec. 2019.

[4] Z. Ning, J. Huang, X. Wang, J. P. C. Rodrigues, and L. Guo, “Mobile Edge Computing-Enabled Internet of Vehicles: Toward Energy-Efficient Scheduling,’’ IEEE Network, vol. 33, no. 5, pp. 198-205, Sept.-Oct. 2019.

[5] F. Jameel, Z. Chang, J. Huang, and T. Ristaniemi, “Internet of Autonomous Vehicles: Architecture, Features, and Socio-Technological Challenges,’’ IEEE Wireless Communications, vol. 26, no. 4, pp. 21-29, Aug. 2019.

Internet of Things

[1] J. Huang, C. Xing, S. Y. Shin, F. Hou, and C. Hsu, “Optimizing M2M Communications and Quality of Services in the IoT for Sustainable Smart Cities,’’ IEEE Transactions on Sustainable Computing, vol. 3, no. 1, pp. 4-15, 1 Jan.-Mar. 2018.

[2] J. Huang, X. Li, W. Wang, K. Hua, and S. Guo, “DTD: A Novel Double-Track Approach to Clone Detection for RFID-Enabled Supply Chains,’’ IEEE Transactions on Emerging Topics in Computing, vol. 5, no. 1, pp. 134-140, Jan.-Mar. 2017.

[3] J. Huang, C. Xing, and C. Wang, “Simultaneous Wireless Information and Power Transfer: Technologies, Applications, and Research Challenges,’’ IEEE Communications Magazine, vol. 55, no. 11, pp.26-32, Nov. 2017.

[4] J. Huang, Q. Duan, Y. Zhao, Z. Zheng, and W. Wang, “Multicast Routing for Multimedia Communications in the Internet of Things,’’ IEEE Internet of Things Journal, vol. 4, no. 1, pp. 215-224, Feb. 2016.

[5] J. Huang, Y. Meng, X. Gong, Y. Liu, and Q. Duan, “A Novel Deployment Scheme for Green Internet of Things,’’ IEEE Internet of Things Journal, vol. 1, no. 2, pp. 196-205, Apr. 2014.

SDN and Cloud Computing

[1] J. Huang, Q. Duan, C. Xing, B. Gu, G. Wang, S. Zeadally, and E. Baker, “A Fine-Grained Video Traffic Control Mechanism in Software-Defined Networks,” IEEE Transactions on Network and Service Management, vol. 19, no. 3, pp. 3501-3515, Sept. 2022.

[2] J. Huang, Q. Duan, S. Guo, Y. Yan, and S. Yu, “Converged Network-Cloud Service Composition with End-to-End Performance Guarantee,’’ IEEE Transactions on Cloud Computing, vol. 6, no. 2, pp. 545-557, Apr.-June 2018.

[3] J. Huang, J. Zou, and C. Xing, “Competitions Among Service Providers in Cloud Computing: A New Economic Model,’’ IEEE Transactions on Network and Service Management, vol. 15, no. 2, pp. 866-877, June 2018.

[4] J. Huang, S. Li, and Q. Duan, “Constructing Multicast Routing Tree for Inter-Cloud Data Transmission: An Approximation Algorithmic Perspective,’’ IEEE/CAA Journal of Automatica Sinica, vol. 5, no. 2, pp. 514-522, Mar. 2018.

[5] G. Wang, Y. Zhao, J. Huang, and W. Wang, “The Controller Placement Problem in Software Defined Networking: A Survey,’’ IEEE Network, vol. 31, no. 5, pp. 21-27, 2017.

QoS Routing and Shortest Path

[1] Q. Wang, H. Jiang, Y. Jiang, S. Yi, L. Li, C. Xing, and J. Huang, “On Searching Multiple Disjoint Shortest Paths in Scale-Free Networks with Hyperbolic Geometry,” IEEE Transactions on Network Science and Engineering, vol. 9, no. 4, pp. 2772-2785, July-Aug. 2022.

[2] J. Huang, Q. Duan, Q. Chen, Y. Sun, Y. Tanaka, and W. Wang, “Guaranteeing End-to-End Quality-of-Service with A Generic Routing Approach,’’ ACM Applied Computing Review, vol. 14, no. 2, pp. 8-22, June 2014.

[3] J. Huang, C. Xu, Q. Duan, Y. Ma, and G.-M. Muntean, “Novel End-to-End Quality of Service Provisioning Algorithms for Multimedia Services in Virtualization-based Future Internet,’’ IEEE Transactions on Broadcasting, vol. 58, no. 4, pp. 569-579, Dec. 2012.

Full Publication List@Google Scholar