Research

Core research directions at EXTEND Lab.

Research Areas

What We Explore

Multi-Agent Systems

Collaborative and competitive intelligence for complex cyber-physical and physical-world tasks.

Robotic/Embodied AI

Agents that perceive, act, adapt, and learn robustly in uncertain and dynamic environments.

Simulation-to-Reality RL

Bridging virtual training environments and physical deployment through robust reinforcement learning pipelines.

Edge Intelligence and Wireless Systems

Learning-enabled communications, resource allocation, and intelligent infrastructure.

Call for Papers

Open Calls and CFPs

Publications

Selected Publications

Journal Papers 24
Conference Papers 17

Latest Journal Articles

  1. X. Zhang, J. Yu*, Z. Zhong, "Learning Efficient Communication Protocols for Multi-Agent Reinforcement Learning," in IEEE Transactions on Machine Learning in Communications and Networking (accepted), July 2026.
  2. H. Xiong, J. Yu*, "Latency-Freshness-Aware Vehicular Edge Computing for Digital Twin-Enabled Intelligent Transportation," in IEEE Transactions on Intelligent Transportation Systems (Minor Revision), Jun. 2026.
  3. C. Shang, D. T. Hoang and J. Yu*, "Scheduling and Fusion for Multimodal Federated Learning in Energy-constrained Wireless Networks," in IEEE Transactions on Mobile Computing (accepted), Jul. 2026.
  4. C. Shang, J. Yu* and D. T. Hoang, "Integrating Brain-Computer Interface and Neuromorphic Computing for Human Digital Twins," in IEEE Communications Magazine, doi: 10.1109/MCOM.001.2500100.
  5. J. Zheng, J. Yu*, X. Liu, "Scheduling and Fusion for Multimodal Federated Learning in Energy-constrained Wireless Networks," in IEEE Transactions on Mobile Computing (accepted), Sep. 2025.
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Latest Conference Papers

  1. Y. Zhang, Z. Zhang, X. Zhang, et al., "A Heterogeneous Multi-Agent Vision-Language Framework for Inductor Defect Recognition in Industrial IoT," 2026 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Singapore, 2026 (accepted).
  2. X. Zhang, Z. Zhong, J. Yu, "Learning Multi-Agent Communication Protocol: Study on Information Entropy Efficiency in MARL," The third Reinforcement Learning Conference (RLC), Montreal, Canada, 2026.
  3. H. Xiong, J. Yu, "Joint Optimization of Latency and Freshness for Digital Twin-Empowered Vehicular Edge Services," 2026 IEEE 103st Vehicular Technology Conference (VTC2026-Spring), Nice, France, 2026.
  4. J. Zheng, J. Yu, X. Liu, "Maximizing Personalized Energy-efficiency for Swarm Learning in 6G Networks," 2026 IEEE International Conference on Communications (ICC), Glasgow, 2026.
  5. C. Shang, D. Hoang, D. Nguyen, J. Yu, "Spiking Personalized Federated Learning for Brain-Computer Interface-Enabled Immersive Communication," 2026 INFOCOM Workshop, Tokyo, 2026.
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