About Me
I’m Junfei Zhan, originally from China, and an incoming PhD student in the Department of Computing at Imperial College London, joining in October 2026 under the supervision of Professor Giuliano Casale. I recently earned my master’s degree in Electrical Engineering at the University of Pennsylvania, where my research was supervised by Professor Saswati Sarkar. My previous research in undergrad was supervised by Professor Tengjiao He and Professor Kwan-Wu Chin.
My research interests center on optimization, Large Language Models (LLMs), and data-driven decision-making, particularly within energy-constrained computing environments. I’ve led and co-authored multiple research projects focused on task scheduling, LLMs, and green IoT networks. I’m passionate about combining mathematical modeling, machine learning, and control theory to tackle real-world system challenges.
Outside of academics, grabbing meals with friends and socializing are among my favorite activities. Sports have also been a significant part of my life, with awards earned in sprinting, rock climbing, rowing, and table tennis.
📄 You can download my full CV here.
📧 Feel free to contact me at:
- Large Language Models
- Optimization
- Network Science
PhD in Computing
Imperial College London, UK
MS in Electrical Engineering
University of Pennsylvania, USA
Dual BSc in Applied Mathematics and Information Computing Science
University of Birmingham, UK & Jinan University, China
- May 10 2026
"Orchestrating Data Collection and Computation in Green IoT Networks" was accepted by the IEEE Internet of Things Journal.
- Apr 27 2026
"Graph Learning-based Update Manipulation Attack on Federated Fine-Tuning of LLMs over Wireless Networks" was accepted to The 24th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys '26 Posters).
- Apr 24 2026
Received the 2026 ESE Department Master's Top 10% GPA Award for outstanding academic performance.
- Feb 13 2026
"Joint Function Configuration and Multislot Offloading in Solar-Powered Serverless Edge Computing" was accepted by the IEEE Internet of Things Journal.
- Jan 16 2026
"SpikeBP: Efficient Spike-Driven Transformer for Blood Pressure Waveform Generation with Frequency Knowledge Distillation" was selected for oral presentation at IEEE ICASSP 2026.
