I am currently an assistant professor in the University of Science and Technology of China. Last year, I received my Ph.D. degree in Hong Kong University of Science and Technology, supervised by Prof. Kai Chen and Prof. Qiang Yang. Before that, I received my B.Eng in biology engineering in 2012 from BUAA and M.Eng. in computer science from SYSU. My research interests are machine learning and its various applications in all possible aspects, including networking, system and privacy computing.

We are looking for PhD/Master students and interns in the area of machine learning, system and networking. If you are interested, please feel free to contact me.

Publications (Google Scholar)

Conference

• Exploiting Student Parallelism for Low-latency GPU Inference of BERT-like Models in Online Services
  Weiyan Wang; Yilun Jin; Yiming Zhang; Victor Junqiu Wei; Han Tian; Li Chen; Jinbao Xue; Yangyu Tao; Di Wang; Kai Chen.
  KDD ‘25

• Towards Optimal Rack-scale μs-level CPU Scheduling through In-Network Workload Shaping
  Xudong Liao; Han Tian; Xinchen Wan; Chaoliang Zeng; Hao Wang; Junxue Zhang; Mengyu Ma; Guyue Liu; Kai Chen.
  ATC ‘25

• Enabling Efficient GPU Communication over Multiple NICs with FuseLink
  Zhenghang Ren; Yuxuan Li; Zilong Wang; Xinyang Huang; Wenxue Li; Kaiqiang Xu; Xudong Liao; Yijun Sun; Bowen Liu; Han Tian; Junxue Zhang; Mingfei Wang; Zhizhen Zhong; Guyue Liu; Ying Zhang; Kai Chen.
  OSDI ‘25

• GREEN: Carbon-efficient Resource Scheduling for Machine Learning Clusters
  Kaiqiang Xu; Decang Sun; Han Tian; Junxue Zhang; Kai Chen.
  NSDI ‘25

• A Generic and Efficient Communication Framework for Message-level In-Network Computing
  Xinchen Wan; Luyang Li; Han Tian; Xudong Liao; Xinyang Huang; Chaoliang Zeng; Zilong Wang; Xinyu Yang; Ke Cheng; Qingsong Ning; Grace Liu; Layong Luo; Kai Chen.
  IEEE INFOCOM ‘25

• Achieving Fairness Generalizability for Learning-based Congestion Control with Jury
  Han Tian; Xudong Liao; Decang Sun; Chaoliang Zeng; Yilun Jin; Junxue Zhang; Xinchen Wan; Zilong Wang; Yong Wang; Kai Chen.
  EuroSys ‘25

• Astraea: Towards Fair and Efficient Learning-based Congestion Control
  Xudong Liao*; Han Tian*(co-first); Chaoliang Zeng; Xinchen Wan; Kai Chen.
  EuroSys ‘24

• Towards Domain-Specific Network Transport for Distributed DNN Training
  Hao Wang; Han Tian; Jingrong Chen; Xinchen Wan; Jiacheng Xia; Gaoxiong Zeng; Wei Bai; Junchen Jiang; Yong Wang; Kai Chen.
  NSDI ‘24

• Accelerating Neural Recommendation Training with Embedding Scheduling
  Chaoliang Zeng; Xudong Liao; Xiaodian Cheng; Han Tian; Xinchen Wan; Hao Wang; Kai Chen.
  NSDI ‘24

• Accelerating Privacy-Preserving Machine Learning With GeniBatch
  Xinyang Huang; Junxue Zhang; Xiaodian Cheng; Hong Zhang; Yilun Jin; Shuihai Hu; Han Tian; Kai Chen.
  EuroSys ‘24

• MDP: Model Decomposition and Parallelization of Vision Transformer for Distributed Edge Inference
  Weiyan Wang; Yiming Zhang; Yilun Jin; Han Tian; Li Chen.
  The 19th International Conference on Mobility, Sensing, and Networking (MSN '23)

• Sphinx: Enabling Privacy-Preserving Online Learning over the Cloud
  Han Tian, Chaoliang Zeng; Zhenghang Ren; Di Chai; Junxue Zhang; Kai Chen; Qiang Yang.
  IEEE S&P ‘22 [Paper]

• Spine: An Efficient DRL-based Congestion Control with Ultra-low Overhead
  Han Tian, Xudong Liao, Chaoliang Zeng, Kai Chen.
  CoNEXT ‘22 [Paper]

• Multi-Objective Congestion Control
  Ma, Yiqing; Han Tian; Xudong Liao; Junxue Zhang; Weiyan Wang; Kai Chen; Xin Jin.
  EuroSys ‘22 [Paper]

Workshop

• Topo-X: Co-optimize Flow Scheduling, Topology, and ML Training Parallelism
  YiXiang Hu; Han Tian; Yifang Zhao; Feng Wu; Xiangyang Li.
  The 2nd International Workshop on Artificial Intelligence Empowered Communication and Networking (AI-CommNet) in conjunction with ICCCN 2025

• Quantifying the Performance of Federated Transfer Learning.
  Qinghe Jing; Weiyan Wang; Junxue Zhang; Han Tian; Kai Chen
  International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (FML’19) in conjunction with IJCAI-19

• Herald: An Embedding Scheduler for Distributed Embedding Model Training.
  Chaoliang Zeng; Xiaodian CHENG; Han Tian; Hao WANG; Kai Chen.
  The 6th Asia-Pacific Workshop on Networking (APNet'22), Fuzhou, China, 1-2, July, 2022.

Journal

• Prediction of peripheral blood lymphocyte subpopulations after renal transplantation
  Bo Peng; Xuyu Xiang; Han Tian; Kaiqiang Xu; Quan Zhuang; Junhui Li; Pengpeng Zhang; Yi Zhu; Min Yang; Jia Liu; Yujun Zhao; Ke Cheng; Yingzi Ming.
  Renal Failure, 2025.

• Distributed Traffic Engineering in Hybrid Software Defined Networks: A Multi-Agent Reinforcement Learning Framework
  Yingya Guo; Bin Lin; Qi Tang; Yulong Ma; Huan Luo; Han Tian; Kai Chen
  IEEE Transactions on Network and Service Management. 2024.
• High-performance Hardware Acceleration Architecture for Cross-silo Federated Learning
  Junxue Zhang; Xiaodian Cheng; Liu Yang; Jinbin Hu; Han Tian; Kai Chen
  Transactions on Parallel and Distributed Systems. 2024.

• Efficient DRL-based Congestion Control with Ultra-low Overhead
  Han Tian; Xudong Liao; Chaoliang Zeng; Decang Sun; Junxue Zhang; Kai Chen.
  IEEE/ACM Transactions on Networking. 2024.

• The study of the association between immune monitoring and pneumonia in kidney transplant recipients through machine learning models.
  Bo Peng; Hang Gong; Han Tian; Quan Zhuang; Junhui Li; Ke Cheng; Yingzi Ming.
  Journal of Translational Medicine, v. 18, (1), 29 September 2020

Experiences and Services

• Journal Reviewer: IEEE Transactions on Networking (ToN), IEEE Transactions on Mobile Computing (TMC), Frontiers of Computer Science (FCS)
• ChinaSys 2025 Program Committee Member
• CoNEXT 2025 Technical Program Committee Member
• Tecent Intern: Shenzhen, China; 2016
• Object Detection with Deep Learning Workshop Lecturer
  HKUST Big Data Institute (BDI), Hong Kong, May 2018
  
• HKSAIR Deep Learning Workshop
  Hong Kong Society of Artificial Intelligence and Robotics (HK-SAIR), Hong Kong, 2018-2020
• Teach assistant at HKUST (2017-Now)
  C++; Computer Architecture; Foundation of Data Analysis