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Dr. TANG Hao (唐 昊)

Research Fellow
College of Computing and Data Science
Nanyang Technological University
Office: N4-B2C-06
Email: howard.haotang_at_gmail.com
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About Me

  Hi there 😄! I'm Hao (Howard) Tang, a currently Research Fellow at the College of Computing and Data Science, Nanyang Technological University with Prof. Adams Wai-Kin Kong. Prior to this, I was a Postdoctoral Fellow at the Centre for Smart Health, The Hong Kong Polytechnic University with Prof. Jing (Harry) Qin. I received my Ph.D. in 2024 from Nanjing University of Science and Technology, where I was supervised by Prof. Jinhui Tang (IAPR Fellow) and co-supervised by Prof. Zechao Li. During my doctoral journey, I have been fortunately advised by and working with Prof. Shengfeng He, Prof. Jun Liu (IAPR Fellow) and Prof. Guo-jun Qi (IEEE/IAPR Fellow). My primary research interests center on Multimodal Large Language Models, Autonomous Agents, and Trustworthy AI, with a particular focus on fine-grained, data-efficient, and robust learning, as well as their applications in AI for Healthcare and AI for Safety. The ultimate goal of my research is to develop reliable and adaptable machines that can learn, reason, and act in Limited, Dynamic, and Imperfect real-world environments like humans.

Recent News

Selected PublicationsGoogle Scholar Citations

BlockMix: Meta Regularization and Self-Calibrated Inference for Metric-Based Meta-Learning
Hao Tang, Zechao Li, Zhimao Peng, and Jinhui Tang
ACM Multimedia 2020 [Code] Oral Presentation
Connecting Giants: Synergistic Knowledge Transfer of Large Multimodal Models for Few-Shot Learning
Hao Tang, Shengfeng He, and Jing Qin
International Joint Conference on Artificial Intelligence 2025 [Code] Oral Presentation
FourierPET: Deep Fourier-based Unrolled Network for Low-count PET Reconstruction
Zheng Zhang, Hao Tang✉, Yingying Hu, Zhanli Hu, and Jing Qin
AAAI Conference on Artificial Intelligence 2026 [Code] Oral Presentation
Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection
Hao Tang, Zechao Li, Dong Zhang, Shengfeng He, and Jinhui Tang
IEEE Transactions on Pattern Analysis and Machine Intelligence [Code] ESI Hot Paper & ESI Highly Cited Paper
Learning Attention-Guided Pyramidal Features for Few-shot Fine-grained Recognition
Hao Tang, Chengcheng Yuan, Zechao Li, and Jinhui Tang
Pattern Recognition [Code] IJCAI LTDL Workshop 2021 Best Paper Award & ESI Highly Cited Paper
Top Cited Paper in Pattern Recognition (One of the most cited articles published since January 2022)

Honors & Awards

Professional Services