Scholar
Wen Wu
Google Scholar ID: TA8_qpgAAAAJ
Associate Researcher, Pengcheng Laboratory, China, IEEE Senior Member
Citations & Impact
Citations
5,105
H-index
32
i10-index
59
Publications
20
Co-authors
13
list available
Contact
Resume (English only)
Academic Achievements
- Paper 'MobiLLM: Enabling On-Device Fine-Tuning of Billion-Sized LLMs via Server-Assisted Side-Tuning' accepted by IEEE JSTSP.
- Paper 'AI-Native Network Digital Twin for Intelligent Network Management in 6G' accepted by IEEE Network.
- Paper 'Adaptive RAN Slicing for Diffusion-based AIGC Services in Mobile Edge Networks' won the IEEE ICCT Best Student Paper Award.
- Paper 'Intelligent Rotatable Antenna for Integrated Sensing, Communication, and Computation: Challenges and Opportunities' accepted by IEEE WCM.
- Named as one of Stanford University's World’s Top 2% Scientists in 2025 (consecutive since 2023).
- Paper 'Collaborative LLM Inference over LEO Satellite Networks: Model Splitting and Pipeline Parallelism' accepted by IEEE WCSP.
- Paper 'Memory-Efficient LLM Fine-Tuning on the Mobile Device via Server Assisted Side Tuning' accepted by ACM Mobicom Workshop.
- Paper 'Demo: Split-and-Pipeline: Collaborative Large Model Inference on Edge Devices' accepted by ACM Mobicom Demo.
- Invited to serve as the Associate Editor of IEEE Transactions on Mobile Computing (CCF A).
- Paper 'Efficient Channel Estimation for Rotatable Antenna-Enabled Wireless Communication' accepted by IEEE Wireless Communications Letter.
- Paper 'Privacy-Aware SFL for Resource-Efficient LLM Fine-Tuning over IoT Devices' accepted by IEEE Internet of Things Journal.
- Paper 'Split-LEO: Efficient AI Model Training over LEO Satellite Networks' accepted by SCIENCE CHINA Information Sciences (CCF A).
- Paper 'AI-assisted Network-slicing based Next-generation Wireless Networks' received the prestigious IEEE Vehicular Technology Society OJVT Best Paper Award (only 1 per year).
- Paper 'Split Fine-Tuning for Large Language Models in Wireless Networks' accepted by IEEE Journal of Selected Topics in Signal Processing (IF: 13.7).
- Paper 'LLM-Empowered IoT for 6G Networks: Architecture, Challenges, and Solutions' accepted by IEEE Internet of Things Magazine.
- Paper 'Efficient Model Training in Edge Networks with Hierarchical Split Learning' accepted by IEEE TMC (CCF A).
Research Experience
- Since 2021, has been working as an Associate Researcher at the Frontier Research Center of Peng Cheng Laboratory and is the Director of PCL INR Lab.
Education
- Received B.E. from South China University of Technology in 2012, M.E. from the University of Science and Technology of China in 2015, and Ph.D. from the University of Waterloo in 2019. Worked as a Postdoctoral Research Fellow in the ECE Department at the University of Waterloo from 2019 to 2021.
Background
- Research interests include 6G networks, network intelligence, and network virtualization. Currently an Associate Researcher at the Frontier Research Center of Peng Cheng Laboratory, and Director of PCL INR Lab (Intelligent Network Research Lab).
Miscellany
- Recruitment information: Recruiting joint PhD students, postdocs, and visiting students.
