Shaoyuan Huang （黄少远）
I’m an Algorithm Engineer in the AI Infrastructure inference team at JD Cloud, JD Technology, and a member of JD’s TGT program. My research focuses on scheduling and resource management for efficient, reliable large language model (LLM) serving.
I received my Ph.D. from Tianjin University, advised by Professor Xiaofei Wang, and visited King’s College London under Professor Yansha Deng, supported by the China Scholarship Council. I also received my B.E. and M.E. degrees from Tianjin University. My earlier research and internships at PPIO (Paiou Cloud) explored workload forecasting and resource provisioning for cloud and edge systems.
My current research centers on Priority- and SLO-aware LLM Inference Scheduling and Heterogeneous Resource Allocation, including routing–scheduling coordination, cost-aware runtime adaptation, and workflow-aware scheduling for agentic applications. I aim to develop principled methods that balance latency, throughput, fairness, and resource efficiency under dynamic workloads and diverse service requirements.
Interests
- Priority- and SLO-aware LLM Inference Scheduling
- Heterogeneous Resource Allocation and Runtime Adaptation
- Workflow-aware Scheduling for Agentic Applications
- Workload Forecasting 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 - 2026
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
- 研究生国家奖学金（博士）National Scholarship for Doctoral Students, 2025
- SIGKDD Student Travel Grant, SIGKDD 2025
- China Scholarship Council, 2025
- CCF DPCS Distinguished Doctorate, CCF Computility 2024
- 比亚迪奖学金 BYD Scholarship, 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 & PC Member
- Session Chair on Workshop on Integrating Edge Intelligence and Large Model in Next Generation Networks (IEILM'24, Colocated with INFOCOM'24)
- PC Member, IEEE International Conference on Distributed Computing Systems (ICDCS 2026)
Organizing Volunteer
- IEEE International Conference on Computer Communications (INFOCOM'25)
Reviewer
Conferences:
- SIGKDD; ICML 2026 Reviewer (Gold Reviewer Award); ICDCS
- IEEE Conference on Vehicular Technology (VTC)
Journals:
- IEEE Transactions on Machine Learning in Communications and Networking (TMLCN)
- IEEE Transactions on Mobile Computing (TMC)
- IEEE Transactions on Cognitive Communications and Networking (TCCN)
- IEEE Network Magazine
- IEEE Networking Letters
- 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🗺️ Places I've Visited
This map shows the cities and countries I have visited around the world. Click on markers to see location names.