Xiao Zhang (张啸)

I am currently an Associate Professor in the School of Computer Science and Technology at Shandong University. I received my Ph.D. degree from the DisLab, School of Computer Science, Nanjing University, advised by Prof. Sanglu Lu and Prof. Wenzhong Li. I received my bachelor's degree in School of Software, Central South University. I was also a visiting student at George-August-University of Goettingen (Working with Prof. Xiaoming Fu), and visiting scholar at Rutgers, the State University of New Jersey (Working with Prof. Hui Xiong). Research Interests Distributed Learning, Federated learning, Edge Intelligence, Big Data Mining. The research topics I am currently interested in include: Distributed Learning/Federated Learning Theory (e.g., Convergence Analysis) in Resource-Limited Edge Environment Heterogeneous Models Collaboration Algorithms Design in Multi-Agent Systems Distributed Learning System Optimization for LLMs on Resource-Limited Edge Multivariate Time Series Analysis, Anomaly Detection Email: xiaozhang@sdu.edu.cn Address: Binhai Road No.72, Jimo District, Qingdao, Shandong, China.

Student Recruitment

We are looking for well motivated Ph.D., Master students and Undergraduate students. Please feel free to drop me an email.

招收博士、硕士研究生和本科科研助理，有较强的学习科研自驱力，有意向同学欢迎通过email发送简历。

对于表现优异的同学，我们将提供参加国内外学术会议、交流访问、升学、实习的机会。

TIPS: We encourage you to showcase your proficient programming skills, good command of English,
and effective communication abilities. We will provide you with various training and guidance to support your steady growth.

Selected Publications(Google Scholar Profile: Xiao Zhang(张啸))

2027

• Yan Li, Xiao Zhang *, Mingyi Li, Mengbai Xiao, Dongxiao Yu.
  Helix: An Efficient Heterogeneity-Aware System for Training LLMs on Consumer-Grade GPUs.
  Accepted to Appear in Proceedings of the 22nd European Conference on Computer Systems (EuroSys 2027). (CCF-A).

2026

• Xiao Zhang, Yangyang Wang, Xingyu Sun, Mingyi Li, Zengzhe Chen, Yuan Yuan, Yifei Zou, Rajiv Ranjan, Xiuzhen Cheng, Dongxiao Yu.
  Alternating Distillation and Resource-Adaptive Pruning for Federated Large Model Adaptation.
  Accepted to Appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026. (CCF-A).

• Mingyi Li, Xiao Zhang *, Zengzhe Chen, Jiawei Zhang, Yuan Yuan, Wei Guo, Fuzhen Zhuang, Dongxiao Yu.
  DeMIC: Decentralized Meta In-Context Learning with Refiner-Guided Adaptation.
  Proceedings of the 32nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2026). (CCF-A).

• Xiao Zhang, Zengzhe Chen, Mingyi Li, Jing Qiao, Yuan Yuan, Fuzhen Zhuang, Dongxiao Yu.
  Forgetting Whenever You Want: A Decentralized Continual Learning Framework with On-Demand Unlearning.
  Proceedings of the 43rd International Conference on Machine Learning (ICML 2026). (CCF-A).

• Ruisheng Zheng, Mingyi Li, Xiao Zhang *, Hongjian Shi, Yanjie Fu, Yuan Yuan, Dongxiao Yu.
  DGTF: Cross-Domain Decentralized Graph Learning with Topology-Aware Knowledge Fusion.
  Proceedings of the 4OthAnnual AAAl Conferenceon Artificial Intelligence (AAAI 2026). (CCF-A).

2025

• Yan Li, Xiao Zhang *, Mingyi Li,Guangwei Xu, Feng Chen, Yuan Yuan, Yifei Zou, Mengying Zhao, Jianbo Lu, Dongxiao Yu.
  Unity is Power: Semi-Asynchronous Collaborative Training of Large-Scale Models with Structured Pruning in Resource-Limited Clients.
  Accepted to Appear in IEEE Transactions on Mobile Computing (TMC), 2025. (CCF-A).

• Xiao Zhang, Qi Wang, Mingyi Li, Yuan Yuan, Mengbai Xiao, Fuzhen Zhuang, Dongxiao Yu.
  TAMO:Fine-Grained Root Cause Analysis via Tool-Assisted LLM Agent with Multi-Modality Observation Data in Cloud-Native Systems.
  Accepted to Appear in IEEE Transactions on Service Computing (TSC), 2025. (CCF-A).

• Wei Guo, Yiqi Tong, Yiyang Duan, Fuzhen Zhuang*, Xiao Zhang*, Zhaojun Hu, Jin Dong.
  FEZE: Alignment-Flexible Zero-Shot Vertical Federated Learning.
  Proceedings of the 31st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2025). (CCF-A).

• Jing Qiao, Yu Liu, Zengzhe Chen, Mingyi Li, Yuan Yuan*, Xiao Zhang*, Dongxiao Yu.
  PDUDT: Provable Decentralized Unlearning under Dynamic Topologies.
  Proceedings of the 42nd International Conference on Machine Learning (ICML 2025). (CCF-A).

• Mingyi Li, Xiao Zhang*, Yuan Yuan, Yifei Zou, Shaoyong Guo, Xiuzhen Cheng, Dongxiao Yu*.
  Generalization-Aware Distributed Minimax Optimization for Large-Scale Models on Resource-Limited Devices.
  Proceedings of the 21st International Conference on Mobility, Sensing and Networking (MSN 2025). (CCF-C, Best Paper Award).

2024

• Xiao Zhang, Shuqing Xu, Huashan Chen, Zekai Chen, Fuzhen Zhuang, Hui Xiong, Dongxiao Yu.
  Rethinking Robust Multivariate Time Series Anomaly Detection: A Hierarchical Spatio-Temporal Variational Perspective.
  Accepted to Appear in IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024. (CCF-A).

• Mingyi Li, Xiao Zhang*, Qi Wang, Tengfei LIU, Ruofan Wu, Weiqiang Wang, Fuzhen Zhuang, Hui Xiong, Dongxiao Yu*.
  Resource-Aware Federated Self-Supervised Learning with Global Class Representations.
  Proceedings of the Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024). (CCF-A).

• Jing Qiao, Shikun Shen, Shuzhen Chen, Xiao Zhang*, Tian Lan, Xiuzhen Cheng, and Dongxiao Yu*.
  De-RPOTA: Decentralized Learning With Resource Adaptation and Privacy Preservation Through Over-the-Air Computation (Extexsion of MobiHoc2023).
  Accepted to Appear in IEEE/ACM Transactions on Networking (TON), 2024. (CCF-A).

• Jing Qiao, Zuyuan Zhang, Sheng Yue*, Yuan Yuan, Zhipeng Cai,Xiao Zhang*, Ju Ren, Dongxiao Yu.
  BR-DeFedRL: Byzantine-Robust Decentralized Federated Reinforcement Learning with Fast Convergence and Communication Efficiency.
  Proceedings of the IEEE International Conference on Computer Communications (INFOCOM 2024). (CCF-A).

2023

• Yangyang Wang, Xiao Zhang*, Mingyi Li, Tian Lan, Huanshan Chen, Hui Xiong, Xiuzhen Cheng, Dongxiao Yu*.
  Theoretical Convergence Guaranteed Resource-Adaptive Federated Learning with Mixed Heterogeneity.
  Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2023). (CCF-A).

• Xiao Zhang, Ziming Ye, Jianfeng Lu, Fuzhen Zhuang, Yanwei Zheng, Dongxiao Yu.
  Fine-Grained Preference-Aware Personalized Federated POI Recommendation with Data Sparsity.
  Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023). (CCF-A).

• Ziming Ye,Xiao Zhang*, Xu Chen, Hui Xiong, Dongxiao Yu.
  Adaptive Clustering based Personalized Federated Learning Framework for Next POI Recommendation with Location Noise.
  Accepted to Appear in IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. (CCF-A).

• Jing Qiao, Shikun Shen, Shuzhen Chen, Xiao Zhang*, Tian Lan, Xiuzhen Cheng, Dongxiao Yu*.
  Communication Resources Limited Decentralized Learning with Privacy Guarantee through Over-the-Air Computation.
  Proceedings of the 24th International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc 2023).(CCF-B, Best Paper Runner-Up Award).

2022

• Zekai Chen, Xiao Zhang*, Xiuzhen Cheng.
  ASM2TV: An Adaptive Semi-Supervised Multi-Task Multi-View Learning Framework for Human Activity Recognition.
  Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI 2022). (CCF-A).

• Zekai Chen, Fangtian Zhong, Qi Luo, Xiao Zhang, Yanwei Zheng.
  Edgevit: Efficient visual modeling for edge computing.
  Proceedings of the International conference on wireless algorithms, systems, and applications (WASA 2022). (CCF-C, Best Paper Award).

2021

• Hongzheng Yu, Zekai Chen, Xiao Zhang *, Xu Chen, Fuzhen Zhuang, Hui Xiong, Xiuzhen Cheng.
  FedHAR: Semi-Supervised Online Learning for Personalized Federated Human Activity Recognition.
  Accepted to Appear in IEEE Transactions on Mobile Computing, 2021. DOI 10.1109/TMC.2021.3136853. (CCF-A, ESI Highly Cited).

• Zekai Chen, Dingshuo Chen, Xiao Zhang*, Zixuan Yuan, Xiuzhen Cheng.
  Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoT.
  Accepted to Appear in IEEE Internet of Things Journal, 2021. DOI 10.1109/JIOT.2021.3100509. (ESI Highly Cited, 2025 IEEE IoT-J Best Paper Runner-Up Award).

2018-2020

• Xiao Zhang, Fuzhen Zhuang, Wenzhong Li, Haochao Ying, Hui Xiong, Sanglu Lu.
  Inferring mood instability via smartphone sensing: a multi-view learning approach.
  in Proc. of the 27th ACM International Conference on Multimedia (ACM MM 2019), 1401-1409, Nice, France, 21 - 25 October 2019. (CCF-A).

• Xiao Zhang, Wenzhong Li, Vu Nguyen, Fuzhen Zhuang, Hui Xiong, Sanglu Lu.
  Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning.
  in Proc. of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018). (CCF-A).

• Xiao Zhang, Wenzhong Li, Xu Chen, and Sanglu Lu.
  MoodExplorer: Towards Compound Emotion Detection via Smartphone Sensing.
  in Proc. of ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 4 (IMWUT/Ubicomp 2018). (CCF-A).

Honors and Award

• Journal of Social Computing 2024-2025 Outstanding Reviewer Award

• ACM QINGDAO Rising Star, 2023

• Program A for Outstanding Ph.D. Candidate of Nanjing University, 2018

• First-Class Ph.D. International Academic Exchange Award of Nanjing University, 2018

• Joint-PhD Student Scholarship of China Scholarship Council, 2017

• Huawei Scholarship, 2017

People

• Students: Mingyi Li (1 NeurIPS, 1 KDD), Yan Li（1 EuroSys, 1 TMC）, Zengzhe Chen (1 ICML) , Mingyu Sun, Tianen Song, Jintao Guo, Zhiyuan Wang, Yuding Mei, Haichuan Liu, Zilong Zhao, Qifei Dai

• Alumni: Qi Wang（MS2026, 1 TSC）, Ruisheng Zheng (BS2026, 1 AAAI), Yangyang Wang (MS2025, 1 KDD, 1 TPAMI), Ziming Ye (MS2024, 1 SIGIR, 1TKDE), Shuqing Xu (MS2024, 1TKDE), Qilin Wang (MS2023, 1 T-ITS), Rongwen Xu (MS2023), Peng Liu (MS2023), Tianli Wang (MS2023), Hongzheng Yu (MS2022, 1 TMC, 1 JBHI), Maiwang Shi (MS2022)