• October 2026: 📝 Two papers were accepted by IEEE IPCCC 2026.
• October 2026: 🤖 Released Component Routing, our work on sending each component of a self-improving GUI agent’s experience to the weights or to the context, as a preprint on arXiv.
• September 2026: 🤖 Released REBASE, our work on keeping the device and cloud copies of GUI-agent experience coherent across app updates, as a preprint on arXiv.
• September 2026: 📝 Our paper “ERRAND: Budgeted Maintenance of Agent Memory” was accepted by NeurIPS WS 2026, Towards Test-Time Continual Learning Agents (arXiv).
• September 2026: 🏆 Our paper “A Review of Continual Learning in Edge AI” was designated as an ESI Highly Cited Paper (Top 1%).
• September 2026: 🏆 Our Discover proposal “Budget-Governed Memory and Post-Deployment Learning for Self-Evolving Language-Model Agents” was approved by NSF ACCESS (PI, 750,000 ACCESS Credits, 2026–2027).
• August 2026: 📝 Our paper “Exposing and Resolving Spurious Isolation in Federated Multimodal Continual Learning” was accepted as a regular paper by the IEEE Transactions on Multimedia.
• August 2026: 📝 Our paper “RELIEF: Turning Missing Modalities into Training Acceleration for Federated Learning on Heterogeneous IoT Edge” was accepted by the IEEE Internet of Things Journal.
• August 2026: 🤖 Released CrystalMem, our work on elastic memory and knowledge crystallization for self-evolving LLM agents, as a preprint on arXiv.
• July 2026: 🤖 Released CURATOR, our work on budget-curated experience memory for self-evolving on-device LLM agents, as a preprint on arXiv.
• July 2026: 🏆 Our paper “Real-time Intelligent Healthcare Enabled by Federated Digital Twins with AoI Optimization” was designated as an ESI Highly Cited Paper (Top 1% in Computer Science).
• April 2026: 📝 Our paper “From Alpha to Omega: Lifecycle-Aware Forgetting Defense in Federated Continual Learning for Planetary Exploration” was accepted by IEEE ICDCS 2026 (acceptance rate: 18.59%).
• April 2026: 📝 Our paper “SCALE: Sensitivity-Aware Federated Unlearning with Information Freshness Optimization for Mobile Edge Computing” was accepted by IEEE ICDCS 2026 (acceptance rate: 18.59%).
• February 2026: 📝 Our paper “``X of Information’’ Continuum: A Survey on AI-Driven Multi-Dimensional Metrics for Next-Generation Networked Systems” was accepted by IEEE Communications Surveys and Tutorials (Impact Factor: 46.7).
• January 2026: 📝 Our paper “A Review of Continual Learning in Edge AI” was accepted by IEEE Transactions on Network Science and Engineering.
• January 2026: 🏆 Our paper “A Fast UAV Trajectory Planning Framework in RIS-assisted Communication Systems with Accelerated Learning via Multithreading and Federating” was designated as an ESI Hot Paper (Top 0.1% in Computer Science).
• December 2025: 📝 Our paper “Reinforcement Learning-Based Energy-Aware Coverage Path Planning for Precision Agriculture” was accepted by ACM RACS 2025.
• October 2025: 📝 Our paper “Enhancing Vehicular Platooning with Wireless Federated Learning: A Resource-Aware Control Framework” was accepted by IEEE/ACM Transactions on Networking.
• June 2025: 🏆 Appointed as Technical Program Committee (TPC) Member for IEEE ICNC 2026.
• June 2025: 📝 Our paper “FedTD3: An Accelerated Learning Approach for UAV Trajectory Planning” was accepted by WASA 2025 (Tokyo, Japan).
• April 2025: 📝 Our paper “Real-time Intelligent Healthcare Enabled by Federated Digital Twins with AoI Optimization” was accepted by IEEE Network Magazine.
• February 2025: 🎉 Our paper “A Fast UAV Trajectory Planning Framework in RIS-assisted Communication Systems” was accepted by IEEE Transactions on Mobile Computing.
• September 2024: 🎓 Started PhD program in Computer Science at South Dakota State University, advised by Prof. Jun Huang.

Journal Articles

• Beining Wu, Jun Huang, Shui Yu. ”``X of Information’’ Continuum: A Survey on AI-Driven Multi-Dimensional Metrics for Next-Generation Networked Systems.” IEEE Communications Surveys and Tutorials (IF: 46.7), 2026.

• Beining Wu, Z. Ding, J. Huang. “A Review of Continual Learning in Edge AI.” IEEE Transactions on Network Science and Engineering, 2026. DOI: 10.1109/TNSE.2026.3657652.
  • ESI Highly Cited Paper (Top 1%)

• Beining Wu, Zihao Ding, Jun Huang. “Exposing and Resolving Spurious Isolation in Federated Multimodal Continual Learning.” IEEE Transactions on Multimedia, 2026. DOI: 10.1109/TMM.2026.3736516.

• Beining Wu, Zihao Ding, Jun Huang. “RELIEF: Turning Missing Modalities into Training Acceleration for Federated Learning on Heterogeneous IoT Edge.” IEEE Internet of Things Journal, 2026. DOI: 10.1109/JIOT.2026.3725593.

• Beining Wu, Jun Huang, Qiang Duan. “Real-time Intelligent Healthcare Enabled by Federated Digital Twins with AoI Optimization.” IEEE Network, 2025. DOI: 10.1109/MNET.2025.3565977.
  • ESI Highly Cited Paper (Top 1% in Computer Science)
• Jun Huang, Beining Wu, Qiang Duan, Liang Dong, Shui Yu. “A Fast UAV Trajectory Planning Framework in RIS-assisted Communication Systems with Accelerated Learning via Multithreading and Federating.” IEEE Transactions on Mobile Computing, 2025. DOI: 10.1109/TMC.2025.3544903.
  • ESI Hot Paper (Top 0.1% in Computer Science)

• Beining Wu, Jun Huang, Qiang Duan, et al. “Enhancing Vehicular Platooning with Wireless Federated Learning: A Resource-Aware Control Framework.” IEEE/ACM Transactions on Networking, 2025. DOI: 10.1109/TON.2025.3625084.

• Beining Wu, Zhengkun Cai, Wei Wu, Xiaobin Yin. “AoI-aware Resource Management for Smart Health via Deep Reinforcement Learning.” IEEE Access, Vol. 11, pp. 81180–81195, 2023.

• Beining Wu, Wei Wu. “Model-Free Cooperative Optimal Output Regulation for Linear Discrete-Time Multi-Agent Systems Using Reinforcement Learning.” Mathematical Problems in Engineering, Vol. 2023, Article ID 6350647, 2023.

• Dong Pan, Beining Wu, Yi-Liu Sun, et al. “A Fault-Tolerant and Energy-Efficient Design of a Network Switch Based on a Quantum-Based Nano-Communication Technique.” Sustainable Computing: Informatics and Systems, Vol. 37, Article 100827, 2023.

Conference Papers

• Beining Wu, Zihao Ding, Jun Huang, Yanxiao Zhao. “Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memory.” IEEE International Performance, Computing, and Communications Conference (IPCCC), 2026.

• Dhe Yeong Tchalla, Beining Wu, Jun Huang, Shuyang Gu, Qiang Duan. “FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning.” IEEE International Performance, Computing, and Communications Conference (IPCCC), 2026.

• Beining Wu, Zihao Ding, Jun Huang. “ERRAND: Budgeted Maintenance of Agent Memory.” NeurIPS WS 2026, Towards Test-Time Continual Learning Agents.

• Beining Wu, Jun Huang, Yanxiao Zhao. “From Alpha to Omega: Lifecycle-Aware Forgetting Defense in Federated Continual Learning for Planetary Exploration.” IEEE International Conference on Distributed Computing Systems (ICDCS), 2026. (Acceptance rate: 18.59%)

• Zihao Ding, Beining Wu, Jun Huang. “SCALE: Sensitivity-Aware Federated Unlearning with Information Freshness Optimization for Mobile Edge Computing.” IEEE International Conference on Distributed Computing Systems (ICDCS), 2026. (Acceptance rate: 18.59%)

• Beining Wu, Zihao Ding, Leo Ostigaard, Jun Huang. “Reinforcement Learning-Based Energy-Aware Coverage Path Planning for Precision Agriculture.” Proceedings of the 2025 International Conference on Research in Adaptive and Convergent Systems (RACS), ACM, 2025.

• Beining Wu, Jun Huang, Qiang Duan. “FedTD3: An Accelerated Learning Approach for UAV Trajectory Planning.” International Conference on Wireless Artificial Intelligent Computing Systems and Applications (WASA), Tokyo, Japan, June 2025.

Preprints

• Beining Wu, Zihao Ding, Jun Huang. “Not All Experience Belongs in the Weights: Component Routing for Self-Improving GUI Agents.” arXiv preprint arXiv:2610.01787, 2026.

• Beining Wu, Jun Huang, Yanxiao Zhao. “REBASE: Device-Cloud Experience Coherence for GUI Agents Across App Updates.” arXiv preprint arXiv:2609.32130, 2026.

• Beining Wu, Jun Huang. “CrystalMem: Elastic Memory for Self-Evolving LLM Agents via Knowledge Crystallization.” arXiv preprint arXiv:2608.00303, 2026.

• Zihao Ding, Beining Wu, Jun Huang. “EASE: Federated Multimodal Unlearning via Entanglement-Aware Anchor Closure.” arXiv preprint arXiv:2605.00733, 2026.

• Zihao Ding, Beining Wu, Jun Huang, Shiwen Mao. “Application-Aware Twin-in-the-Loop Planning for Federated Split Learning over Wireless Edge Networks.” arXiv preprint arXiv:2604.26105, 2026.

• Beining Wu, Jun Huang. “Lifecycle-Aware Federated Continual Learning in Mobile Autonomous Systems.” arXiv preprint arXiv:2604.20745, 2026.