Hailiang ZHAO

Biography

I am a ZJU 100 Young Professor (平台“百人计划”研究员) in the School of Software Technology, Zhejiang University (ZJU). I obtained my PhD from the College of Computer Science and Technology at ZJU in June 2024, supervised by Prof. Shuiguang Deng. From September 2022 to September 2023, I was a visiting PhD student at the PDCL Lab, Nanyang Technological University (NTU), under the supervision of Prof. Xueyan Tang.

[Google Scholar] [ResearchGate] [ZJU Homepage] [CV]

Research Interests

• Learning-Augmented Algorithms & Systems. My research investigates how to integrate machine learning predictions into classic algorithmic frameworks to improve decision-making in uncertain and dynamic environments (see Learning-Augmented Systems). Representative contributions include the algorithm PFSUM (NeurIPS '24) for the classic Bahncard problem, and a robustification framework Guard (NeurIPS '25) for the online caching problem. These algorithms are designed not only for theoretical guarantees but also for real-world computer systems such as MLSys, microservices platforms, and heterogeneous job schedulers. I further explore embedding these techniques into system control loops to support predictive autoscaling, dynamic load dispatching, and low-latency request handling under highly non-stationary workloads.

• Industrial Intelligence. I also work on intelligence systems for industrial and manufacturing applications, with a focus on multimodal data fusion, production task scheduling, and resource optimization. My research addresses how to unify temporal, structured, and perceptual signals from discrete manufacturing processes to enable adaptive, learning-driven decision making (see this slide). I explore constructing dynamic interaction graphs among machines, materials, and operators to support real-time scheduling and flow control in complex production environments. Additionally, I am investigating the development and deployment of vertical-domain foundation models for industrial scenarios such as fault detection, quality control, and equipment maintenance. These models aim to provide reliable semantics-aware decision support for high-throughput and resilient industrial systems.

If you are interested in my research and would like to pursue a Master's or Ph.D. under my supervision, please feel free to send an email to: hliangzhao {AT} zju {DOT} edu {DOT} cn.

Selected Papers

• Ziqi Wang, Hailiang Zhao*, Cheng Bao, Wenzhuo Qian, Yuhao Yang, Xueqiang Sun, and Shuiguang Deng*, XFMNet: Decoding Cross-Site and Nonstationary Water Patterns via Stepwise Multimodal Fusion for Long-Term Water Quality Forecasting. In: arXiv preprints.

• Wenzhuo Qian, Hailiang Zhao*, Tianlv Chen, Jiayi Chen, Ziqi Wang, Kingsum Chow, and Shuiguang Deng*, Learning Unified System Representations for Microservice Tail Latency Prediction. In: arXiv preprints.

• Peng Chen, Hailiang Zhao*, Jiaji Zhang, Xueyan Tang, Yixuan Wang, and Shuiguang Deng*, Toward a Lightweight and Robust Design for Caching. To be proceeded in the 39th Conference on Neural Information Processing Systems (NeurIPS '25).

• Hailiang Zhao, Xueyan Tang*, Peng Chen, Jianwei Yin, and Shuiguang Deng, Data-Locality-Aware Task Assignment and Scheduling for Distributed Job Executions. In: IEEE Transactions on Services Computing (TSC), early access, doi: 10.1109/TSC.2025.3594158. [Code]

• Yinuo Deng, Hailiang Zhao*, Dongjing Wang, Peng Chen, Wenzhuo Qian, Jianwei Yin, Schahram Dustdar, and Shuiguang Deng*, Accelerating Containerized Service Delivery at the Network Edge. In: arXiv preprints.

• Jiaji Zhang, Ruichao Sun, Hailiang Zhao*, Jiaju Wu, Peng Chen, Hao Li, Yuying Liu, Kingsum Chow, Gang Xiong, and Shuiguang Deng*, SegQuant: A Semantics-Aware and Generalizable Quantization Framework for Diffusion Models. In: arXiv preprints.

• Hailiang Zhao, Ziqi Wang, Guanjie Cheng*, Wenzhuo Qian, Peng Chen, Jianwei Yin, Schahram Dustdar, and Shuiguang Deng, Online Workload Scheduling for Social Welfare Maximization in the Computing Continuum. In: IEEE Transactions on Services Computing (TSC), early access, doi: 10.1109/TSC.2025.3570845.

• Fan'an Meng, Hongjun Dai*, Guoqing Cong, Bo Zhu, and Hailiang Zhao, CATScaler: A Convolution-Augmented Transformer Scaling Framework for Cloud-Native Applications. In: IEEE Transactions on Services Computing (TSC), early access, doi: 10.1109/TSC.2025.3592383.

• Cheng Zhang, Yinuo Deng, Hailiang Zhao*, Tianlv Chen, and Shuiguang Deng*, Tail-Learning: Adaptive Learning Method for Mitigating Tail Latency in Autonomous Edge Systems. In: ACM Transactions on Autonomous and Adaptive Systems (TAAS), early access, doi: https://doi.org/10.1145/3737289.

• Zhiwei Ling, Yachen Chang, Hailiang Zhao*, Xinkui Zhao, Kingsum Chow*, and Shuiguang Deng, CADRef: Robust Out-of-Distribution Detection via Class-Aware Decoupled Relative Feature Leveraging. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2025 (CVPR '25). [Code] [Poster]

• Hailiang Zhao, Xueyan Tang, Peng Chen, and Shuiguang Deng, Learning-Augmented Algorithms for the Bahncard Problem. In: Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS '24). [Code] [Slide] [Poster]

• Shuiguang Deng*, Hailiang Zhao*, Bingbing Huang, Cheng Zhang, Feiyi Chen, Yinuo Deng, Jianwei Yin, Schahram Dustdar, and Albert Y. Zomaya, Cloud-Native Computing: A Survey from the Perspective of Services. In: Proceedings of the IEEE (JPROC), vol. 112, no. 1, pp. 12-46, Jan. 2024, doi: 10.1109/JPROC.2024.3353855.

• Hailiang Zhao, Shuiguang Deng*, Zhengzhe Xiang, Xueqiang Yan, Jianwei Yin, Schahram Dustdar, and Albert Y Zomaya, Scheduling Multi-Server Jobs with Sublinear Regrets via Online Learning. In: IEEE Transactions on Services Computing (TSC), vol. 17, no. 3, pp. 1168-1180, May-June 2024, doi: 10.1109/TSC.2023.3303344.

• Hailiang Zhao, Shuiguang Deng*, Feiyi Chen, Jianwei Yin, Schahram Dustdar, and Albert Y. Zomaya, Learning to Schedule Multi-Server Jobs with Fluctuated Processing Speeds. In: IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 34, no. 1, pp. 234-245, 1 Jan. 2023, doi: 10.1109/TPDS.2022.3215947. [Slide]

• Shuiguang Deng, Hailiang Zhao, Zhengzhe Xiang, Cheng Zhang, Rong Jiang, Ying Li*, Jianwei Yin, Schahram Dustdar, and Albert Y. Zomaya, Dependent Function Embedding for Distributed Serverless Edge Computing. In: IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 17, no. 3, pp. 1168-1180, May-June 2024, doi: 10.1109/TPDS.2021.3137380.

• Hailiang Zhao, Shuiguang Deng*, Zijie Liu, Zhengzhe Xiang, Jianwei Yin, Schahram Dustdar, and Albert Y. Zomaya, DPoS: Decentralized, Privacy-Preserving, and Low-Complexity Online Slicing for Multi-Tenant Networks. In: IEEE Transactions on Mobile Computing (TMC), vol. 21, no. 12, pp. 4296-4309, 1 Dec. 2022, doi: 10.1109/TMC.2021.3074934. [Slide]

• Hailiang Zhao, Shuiguang Deng*, Zijie Liu, Jianwei Yin, and Schahram Dustdar, Distributed Redundant Placement for Microservice-based Applications at the Edge. In: IEEE Transactions on Services Computing (TSC), vol. 15, no. 3, pp. 1732-1745, 1 May-June 2022, doi: 10.1109/TSC.2020.3013600. [Slide] (ESI Highly Cited Paper)

• Shuiguang Deng, Hailiang Zhao, Weijia Fang*, Jianwei Yin, Schahram Dustdar, and Albert Y. Zomaya, Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence. In: IEEE Internet of Things Journal (IoTJ), vol. 7, no. 8, pp. 7457-7469, Aug. 2020, doi: 10.1109/JIOT.2020.2984887. (ESI Hot Paper, ESI Highly Cited Paper)

• Hailiang Zhao, Shuiguang Deng*, Cheng Zhang, Wei Du, Qiang He, and Jianwei Yin, A Mobility-aware Cross-edge Computation Offloading Framework for Partitionable Applications. In: Proceedings of the 17th IEEE International Conference on Web Services (ICWS '19), Milan, Italy, 2019. [Slide] [Theoretical Analysis] (Best Student Paper)

Selected Projects

• 全要素互联结构自适应的多模态数据治理技术体系，国家重点研发计划课题，主持 (2024-2027)
• 基于软硬件协同的服务调度与资源管理优化方法研究，国家自然科学基金青年科学基金项目（C类），主持 (2026-2028)
• 面向生成式 AI 的异构硬件资源优化与计算加速理论与方法，浙江省科技厅自然科学基金重大项目，参与 (2025-2027)
• 鲲鹏通用计算性能调优研究技术合作项目，华为技术合作项目，参与 (2024-2025)
• 快手推理场景下典型 GPU 服务的吞吐量提高，快手技术合作项目，共同主持 (2024-2025)
• 面向异构集群的微服务性能分析与资源调度，字节跳动技术合作项目，参与 (2025-2026)
• 6G 网络数据面性能建模与评估项目（二期），华为技术合作项目，参与 (2025-2028)

Selected Awards & Honors

• CCF 中国服务计算创新大赛暨深信服杯算法竞赛决赛二等奖（指导学生获奖） (2025)
• CCF 服务计算专委博士学位论文激励计划 (2025)
• 浙江大学启真优秀青年学者 (2024)
• 浙江大学优秀博士学位论文 (2024)
• 浙江大学博新奖学金 (2019)
• 2019 IEEE International Conference on Web Services 最佳学生论文奖 (2019)
• 武汉理工大学卓越奖学金 (校最高学生奖励) (2018)

Professional Services

I am serving as chair, program chair member and reviewer for several conferences/workshops/forums and journals.

• 1st International Workshop on Service Intelligence for Collaborative Industry, ICSOC '25, chair & co-proposer
• Forum on Intelligent Industrial Internet Technology Based on Human/Thing/Business Interconnection and Cross-Platform Integration, ICSS '25, chair & co-proposer
• AAAI '26, IJCAI '25, ECAI '25, etc., PC member & reviewer; NeurIPS '25, CVPR '24, etc., reviewer
• TSC, 计算机学报, FGCS, TKDD, Scientific Reports, TGCN, IoTJ, MONET, etc., reviewer

Some Research Materials & Resources

• Understanding Acceleration Opportunities for Microservice Overheads at Hyperscale (Jun 2024)
• Characterizing Microservice Dependency and Performance: Alibaba Trace Analysis (May 2024)
• Online Interval Scheduling (Mar 2024)
• Transformation Techniques in Optimization (Feb 2024)
• Everything about ADMM (Nov 2022)
• Distributed Systems in One Slide (Oct 2022)
• ADMM: The Variational Inequality Perspective (Oct 2022)
• An Overview of Kubernetes Scheduling (Oct 2022)
• 优化算法复杂度分析 (Oct 2022)
• 最优化理论基础 (Jul 2021)
• Park: An Open Platform for Learning-Augmented Computer Systems (Jan 2021)
• 理解共轭梯度法 (Jul 2020)
• 需要熟练掌握的算法理论基础 (May 2020)
• How Should I Slice My Network? (Dec 2019)
• 李雅普诺夫优化导论 (Nov 2018)

Correspondence

Emails: hliangzhao {AT} ZJU {DOT} edu {DOT} cn, hliangzhao97 {AT} gmail {DOT} com

Address:

• Room 3#403, Ningbo Campus of Zhejiang University (浙江省宁波市鄞州区学府路 5 号, 浙江大学宁波国际科创中心 (宁波校区) 315100)
• Room 422, Cao Guangbiao Sci-tech Building, Yuquan Campus of Zhejiang University (中国浙江省杭州市西湖区浙大路 38 号，浙江大学玉泉校区 310027)