Biography
I’m a 3rd-year Ph.D. student in the Edge Intelligence Group at Tianjin University, advised by Professor Xiaofei Wang. I’m also a visiting Ph.D. student at the Department of Engineering, King’s College London (under China Scholarship Council), where I collaborate under the supervision of Professor Yansha Deng.
Before my Ph.D., I received my B.E. and M.E. degrees from Tianjin University, both from the College of Intelligence and Computing. I have also completed two industrial internships at PPIO (Paiou Cloud), where I developed large-scale workload prediction models and integrated intelligent task deployment systems.
I’m passionate about building intelligent, high-performance (high-throughput and SLO-compliant) cloud and edge infrastructures, especially in dynamic multi-tenant environments. Recently, I’ve been working on LLM-adaptive Workload Forecasting and Unified Frameworks for LLM Inference and Fine-tuning across distributed platforms.
Interests
- Distributed System Workload Forecasting
- Resource Provisioning
- AI Inference Serving Systems
- LLM Workload Characterization and Performance Modeling
Education
Visiting Ph.D. in Engineering, 2024.10 - 2025.10
King's College London (UK) | Advisor: Prof. Yansha Deng
Ph.D. in Computer Science, 2022 - Present
Tianjin University | Advisor: Prof. Xiaofei Wang
M.S. in Computer Science, 2020 – 2022
Tianjin University | Advisor: Prof. Xiaofei Wang
B.E. in Computer Science, 2016 – 2020
🏆 Awards & Honors
China Scholarship Council
2025
CCF DPCS Distinguished Doctorate
CCF Computility 2024
比亚迪奖学金
BYD, 2024
Suzhou Talent Scholarship
Suzhou Government Talent Group, 2023 & 2021
Merit Student
Tianjin University, 2023, 2021, 2019, 2018, 2017
Outstanding Graduate
Tianjin University, 2020
🎓 Academic Service
Session Chair
- Session Chair on Workshop on Integrating Edge Intelligence and Large Model in Next Generation Networks (IEILM'24, Colocated with INFOCOM'24)
Organizing Volunteer
- IEEE International Conference on Computer Communications (INFOCOM'25)
Reviewer
Conferences:
- SIGKDD 2023, 2024, 2025
- IEEE Conference on Vehicular Technology (VTC)
Journals:
- IEEE Transactions on Mobile Computing (TMC)
- IEEE Network Magazine
- Artificial Intelligence Review
💼 Internship
Algorithm Development Intern
PPIO/Paiou Cloud Computing (Shanghai) Co.
- 2021.09 - 2022.01: Development of cloud server workload analysis and prediction algorithms; Server utilization impact feature mining
- 2022.03 - 2022.06: System integration of prediction algorithms; Task deployment recommender system development
🚀 Open Source Projects
MetaEformer
Official release (v1.0) of MetaEformer, a generic framework for load forecasting in complex and dynamic systems, accepted at KDD 2025.
📁 View on ZenodoEdge Cloud Server Latency Measurements
Large-scale edge cloud latency measurement dataset and analysis tools for performance optimization research.
📁 View on GitHubDynEformer
Edge Cloud Server Workload Prediction Framework using advanced transformer architectures for dynamic environments.
📁 View on GitHubECW Dataset
Comprehensive Edge Cloud Server Workload Dataset for machine learning research and system optimization.
📁 View on GitHub