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Welcome to the official repository of Qihao Li. I am an associate professor at the College of Communication Engineering, Jilin University, China. My research interests lie in the fields of industrial Internet, digital twin, optimal control and optimization, wireless network security, and localization.

• Ph.D. in Electrical and Computer Engineering
  • University of Oslo, Norway, 2019
• M.Sc. in Information and Communication Technology
  • University of Agder, Norway, 2013

• Associate Professor
  • College of Communication Engineering, Jilin University, China 2023-Current
• Postdoctoral Fellow
  • Department of Electrical and Computer Engineering, University of Waterloo, ON, Canada, 2020-2021
• Visiting Researcher
  • Department of Electrical and Computer Engineering, University of Waterloo, ON, Canada, 2016

• "Tang Aoqing" Distinguished Young Scholar Award, 2023
• "NetInfo Communication for Future Forum" Best Candidate in Open Competition, 2023
• "Dongguan Strategic Scientists" Team Member, 2023

My current research focuses on:

• Industrial Internet
• Digital Twin
• Optimal Control and Optimization
• Wireless Network Security and Localization

• Associate Editor

  • IEEE Internet of Things Journal

• Workshop Technical Program Committee (TPC) Chair

  • IEEE Globecom’24
  • IEEE CIC/ICCC’24
  • IEEE CIC/ICCC’23

• TPC Member

  • IEEE Globecom (2019-2024)
  • IEEE ICC (2019-2024)
  • IEEE CIC ICCC (2017-2024)
  • EuCAP (2019)
  • BDEC-SmartCity (2018)

Refereed Journal Papers

[J1] Q. Li, J. Chen, M. Cheffena, X. Shen, “Channel-Aware Latency Tail Taming in Industrial IoT,” IEEE Trans. on Wireless Commun., vol.22, no. 9, page 6107-6123, 2023.
[J2] Q. Li, N. Zhang, M. Cheffena, X. Shen, “Channel-based Optimal Back-off Delay Control in Delay-Constrained Industrial WSNs,” IEEE Trans. on Wireless Commun., vol. 19, no. 1, page 696-711, 2020.
[J3] Q. Li, M. Cheffena, “Exploiting Dispersive Power Gain and Delay Spread for Sybil Detection in Industrial WSNs: A Multi-Kernel Approach,” IEEE Trans. on Wireless Commun., vol. 18, no. 3, page 1805-1818, 2019. [J4] Y. Bi, R. Fu, C. Jiang, G. Han, Z. Yin, L. Zhao, Q. Li, “Single Source Cross-Domain Bearing Fault Diagnosis via Multi-Pseudo Domain Augmented Adversarial Domain-Invariant Learning,” IEEE Internet of Things, Early Access, DOI: 10.1109/JIOT.2024.3421326, 2024.
[J5] Z. Li, F. Hu, Q. Li, Z. Ling, Z. Chang, and Timo Hamalainen, “AoI-Aware Waveform Design for Cooperative Joint Radar-Communications Systems with Online Prediction of Radar Target Property,” IEEE Trans. on Commun., Early Access, DOI: 10.1109/TCOMM.2024.3392748, 2024.

Refereed Conference Papers

[C1] Q. Li, F. Hu, “Digital Twin-enabled Channel Access Control in Industrial IoT” in Proc. IEEE/CIC ICCC 2024 (Best Paper Award).
[C2] Q. Li, M. Li, N. Zhang, F. Hu, “Digital twin-enabled Channel Access and Power Control Optimization in Industrial IoT” in Proc. IEEE Globecom 2024.
[C3] Q. Li, M. Li, J. Kang, F. Hu, “Digital twin-based Intrusion Detection in Smart Grid: A Multi-kernel Knowledge Replay Approach” in Proc. IEEE Globecom 2024.
[C4] H. Liu, M. Li, F. Gu, Q. Li, W. Zhang, S. Guo, “End-to-end Flow Scheduling Optimization for Industrial 5G and TSN Integrated Networks”, in Proc. IEEE Globecom 2024.
[C5] Z, Li, F. Hu, Z. Ling, S. Song, Q. Li, “Sensing-Communication Trade-off in Vehicular Network with Spatially-Spread OTFS Modulation: An AoI-and-CRB-based Power Allocation Scheme”, in Proc. IEEE Globecom 2024.
[C6] X. Su, M. Li, Q. Li, C. Chen, S. Guo, X. Wang, “Energy Consumption Prediction for Manufacturing in Industrial IoT Based on Heterogeneous GNN”, in Proc. IEEE/CIC ICCC 2024.
[C7] T. Yang, Q. Li, F. Hu, “Intelligent Congestion Control in QUIC for Reliable E2E Communication Network: A Digital Twin-based Approach,” in Proc. IEEE/CIC ICCC 2024.
[C8] J. Liao, J. Wen, J. Kang, Y. Zhang, J. Du, Q. Li, W. Zhang, D. Yang, “Optimizing Information Propagation for Blockchain-empowered Mobile AIGC: A Graph Attention Network Approach”, in Proc. IEEE IWCMC 2024.
[C9] T. Yang, Q. Li, N. Zhang, L. Zhao, F. Hu, “Efficient Federated Learning in Mobile Vehicular Networks: Intelligent User Selection and Resource Optimization”, in Proc. IEEE VTC 2024.

• Email: [email protected]
• Institutional Address: College of Communication Engineering, Jilin University, China

Thank you for visiting my repository. I look forward to potential collaborations and engagements in the field of intelligent networking communications and beyond.