Profile Photo

Dr. TANG Hao (唐 昊)

Centre for Smart Health, Postdoctoral Fellow
The Hong Kong Polytechnic University
Office: Room FJ-505, Chan Tai Ho Building
Email: howard.haotang_at_gmail.com
Google ScholarGithubWeChat

njust_logo njust_logo

About Me

  Hi there 😄! I'm Hao (Howard) Tang, currently a postdoctoral fellow at Centre for Smart Health, The Hong Kong Polytechnic University with Prof. Jing (Harry) Qin. Prior to this, 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 and Prof. Guo-jun Qi (IEEE/IAPR Fellow). My primary research interests include machine learning, computer vision, and medical image analysis, with a particular focus on fine-grained learning, data-efficient learning, and multi-modal learning, as well as their practical applications. The ultimate goal of my research is to develop machines that can learn from Limited, Dynamic, and Imperfect data in real-world scenes like humans.
I am always open to meeting new people and exploring potential collaborations. We are actively seeking motivated Ph.D., M.S., and undergraduate students to work with Prof. Qin and me through research assistantships, visiting positions, or remote internships in AI for Medicine. If you are interested in collaborating or would like to get in touch, please feel free to email me or connect with me on WeChat !😊

Recent News

Selected Publications

BlockMix: Meta Regularization and Self-Calibrated Inference for Metric-Based Meta-Learning
Hao Tang, Zechao Li, Zhimao Peng, and Jinhui Tang
ACM Multimedia 2020 Oral Presentation
M3Net: Multi-view Encoding, Matching, and Fusion for Few-shot Fine-grained Action Recognition
Hao Tang, Jun Liu, Shuanglin Yan, Rui Yan, Zechao Li, and Jinhui Tang
ACM Multimedia 2023 [Code]
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 Oral Presentation
Cross-modal Proxy Evolving for OOD Detection with Vision-Language Models
Hao Tang, Yu Liu, Shuanglin Yan, Fei Shen, Shengfeng He, and Jing Qin
AAAI Conference on Artificial Intelligence 2026
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)
Dual-view Fusion for Fine-grained Image Recognition with Vision Transformer
(基于视觉Transformer的双视图融合细粒度图像识别)
Hao Tang (唐昊), Zechao Li (李泽超), Xin Jiang (蒋鑫), and Jinhui Tang (唐金辉)
Journal of Software (软件学报) [Code]

Honors & Awards

Professional Services