Hi, I am Hongduan Tian, a third-year Ph.D. student at Trustworthy Machine Learning and Reasoning (TMLR) Group in Department of Computer Science, Hong Kong Baptist University, advised by Dr. Bo Han, and work closely with Dr. Feng Liu. Before that, I got my master degree from Nanjing University of Information Science and Technology (NUIST) and was fortunately supervised by Prof. Xiao-Tong Yuan and Prof. Qingshan Liu.
My research focuses on developing trustworthy foundation model agents that can achieve good performance on various tasks. This refers to two aspects: versatile foundation models and trustworthy reasoning paradigms. My work involves explore the underlying mechanisms of learning (e.g., learning dynamic (cf. Yi Ren) and learning mechanism) and reasoning paradigms and building more effective and effecicint agentic frameworks. Previously, I also explore test-time adaptation across various domains. Here are some representative works:
-
Foundation Model Agents: Building FM agentic frameworks.
[MAD-M$^2$] [LangPINN] -
Test-time Adaptation with Limited Samples: Achieving good generalization performance on tasks from previous data or domains.
[MOKD] [CoPA] [IFR]
We are also organizing the TMLR Young Scientist Seminars and actively seeking researchers interested in sharing their work. If you would like to give a talk, we encourage you to reach out to us.
Please feel free to email me for research, collaborations, or a casual chat.
Email: cshdtian [at] comp.hkbu.edu.hk / hongduan.tian [at] gmail.com
📣 News
- $\frak{2026.03}$: I will work as visiting student at RIKEN Imperfect Information Learning Team.
- $\frak{2026.03}$: Our paper “Lang-PINN: From Language to Physics-Informed Neural Networks via a Multi-Agent Framework” is accepted by ICLR 2026 Workshop on AI with Recursive Self-Improvement and is highlighted as Spotlight.
- $\frak{2026.01}$: Our paper “Multi-Agent Debate with Memory Masking” is accepted by ICLR 2026.
- $\frak{2025.11}$: Our paper “Cross-domain Few-shot Classification via Invariant-content Feature Reconstruction” is accepted by IJCV.
- $\frak{2024.09}$: Our paper “Mind the gap between prototypes and images in cross-domain finetuning” is accepted by NeurIPS 2024.
- $\frak{2024.05}$: Our paper “MOKD: Cross-domain finetuning for few-shot classification via maximizing optimized kernel dependence” is accepted by ICML 2024.
📖 Educations
- 2023.09 - present, Hong Kong Baptist University (HKBU), Ph.D. in Computer Science.
- 2018.09 – 2021.06, Nanjing University of Information Science and Technology (NUIST), M.E. in Control Engineering.
- 2014.09 - 2018.06, Nanjing University of Information Science and Technology (NUIST), B.E. in Automation.
📝 Publications
✉️ Corresponding author.
Liangliang You, Xin He, Hongduan Tian, Bo Han, Ivor Tsang, Yew-Soon Ong.
Hongduan Tian, Xiao Feng, Ziyuan Zhao, Xiangyu Zhu, Rolan Yan, Bo Han✉️.
Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han✉️.
Hongduan Tian, Feng Liu, Tongliang Liu, Bo Du, Yiu-ming Cheung, Bo Han✉️.
🎖 Awards
- 2024.11, Research Performance Award, HKBU CS Department.
- 2024.10, NeurIPS Scholar Award.
🎤 Invited Talks
- 2024.11, Mind the Gap Between Prototypes and Images in Cross-domain Finetuning @AI TIME, Online. [Video]
- 2024.06, MOKD: Cross-domain finetuning for few-shot classification via maximizing optimized kernel dependence @AI TIME, Online. [Video]
💻 Services
- Conference Reviewer for ICML, NeurIPS, ICLR, AISTATS.
- Journal Reviewer for TPAMI, TNNLS, TMLR, NEUNET.
🏫 Teaching
- COMP7930 (G) Big Data Analytics, Sem. 2, 2025 - 2026
- COMP7015 (G) Artificial Intelligence, Sem. 1, 2025 - 2026
- COMP7250 (G) Machine Learning, Sem. 2, 2024 - 2025
- COMP7180 (G) Quantitative Methods for Data Analytics and Artificial Intelligence, Sem. 1, 2024 - 2025
- COMP7940 (G) Cloud Computing, Sem. 2, 2023 - 2024
📖 Academic Experiences
- 2026.03 - 2026.06, Visiting student @RIKEN Imperfect Information Learning Team, advised by Dr. Takashi Ishida and Prof. Masashi Sugiyama.
- 2023.09 - present, PhD student @HKBU-TMLR Group, advised by Dr. Bo Han.
- 2022.07 - 2023.05, Research intern @HKBU-TMLR Group, advised by Dr. Bo Han and Dr. Feng Liu.
🏢 Industrial Experiences
- 2024.11 - 2026.04, Remote Research Intern @WeChat, supervised by Xiangyu Zhu and Rolan Yan
- 2022.07 - 2025.12, Research Intern @NVIDIA NVAITC, host by Charles Cheung.
- 2024.06 - 2024.08, Research Intern @WeChat, host by Xiangyu Zhu and Rolan Yan
- 2023.07 - 2023.08, Research Intern @Alibaba.
- 2021.07 - 2022.07, Algorithm Engineer @ZTE Nanjing Research and Development Center.
