I’m currently a second year PhD student at The University of Hong Kong, supervised by Prof. Lequan Yu. I obtained my MPhil degree in Zhejiang University in 2023 and the B.Eng degree in Harbin Institute of Technology in 2020.
My research lies at the intersection of artificial intelligence and healthcare. I am dedicated to designing advanced machine learning algorithms for healthcare and medical image analysis. Currently, I mainly focus on deep learning algorithms for whole slide image analysis.
I am also a machine learning competition enthusiast and a Kaggle Competitions Master (🥇×2, 🥈×2).
News
- 2024.09: 🔥 One paper was accepted by IEEE Transactions on Medical Imaging (TMI)!
- 2024.09: 🔥 One paper was accepted by NeurIPS 2024!
- 2024.08: 🔥 One paper was accepted by Medical Image Analysis (MIA)!
- 2024.08: 🔥 One paper was accepted by Progress in Neuro-Psychopharmacology and Biological Psychiatry (PNP)!
- 2023.07: One paper was accepted by ICCV 2023!
- 2023.07: One paper was accepted by Information Fusion (IF 17.56)!
- 2023.05: Won a Gold Medal (7/1165) in “Google - Isolated Sign Language Recognition” Competition!
- 2023.02: One paper was accepted by Medical Image Analysis (MIA)!
- 2023.02: One paper was accepted by ICASSP 2023!
- 2022.09: Won a Gold Medal (4/1175) in Kaggle “Hacking the Human Body” Competition!
Publications
Yanyan Huang, Weiqin Zhao, Yihang Chen, Yu Fu, Lequan Yu.
Conference on Neural Information Processing Systems (NeurIPS), poster, 2024
Present Concept Anchor-guided Task-specific Feature Enhancement (CATE), an adaptable paradigm that can boost the expressivity and discriminativeness of pathology foundation models for specific downstream tasks.
Yanyan Huang, Weiqin Zhao, Yu Fu, Lingting Zhu, and Lequan Yu.
IEEE Transactions on Medical Imaging (TMI), 2024
This paper introduces a new Pathology Mamba (PAM) for more accurate and robust WSI analysis. It includes three carefully designed components to tackle the challenges of enormous image size, the utilization of local and hierarchical information, and the mismatch between the feature distributions of training and testing during WSI analysis.
Yanyan Huang, Weiqin Zhao, Shujun Wang, Yu Fu, Yuming Jiang, Lequan Yu.
International Conference on Computer Vision (ICCV), poster, 2023
Propose the first continual learning framework for WSI analysis, named ConSlide, to tackle the challenges of enormous image size, utilization of hierarchical structure, and catastrophic forgetting by progressive model updating on multiple sequential datasets.
OTFPF: Optimal Transport Based Feature Pyramid Fusion Network for Brain Age Estimation
Yu Fu$^{*}$, Yanyan Huang$^{*}$, Zhe Zhang, Shunjie Dong, Le Xue, Meng Niu, Yunxin Li, Zhiguo Shi, Yalin Wang, Hong Zhang, Mei Tian, Cheng Zhuo.
Information Fusion (IF), 2023
Propose the Optimal Transport based Feature Pyramid Fusion (OTFPF) network for estimating brain age using T1 MRIs. Experimental results utilizing a dataset of 12,909 MRIs from individuals aged 3–97 years demonstrate the accurate estimation of brain age by the OTFPF network.
HDNet: Hierarchical Dynamic Network for Gait Recognition using Millimeter-Wave Radar
Yanyan Huang, Yong Wang, Kun Shi, Chaojie Gu, Yu Fu, Cheng Zhuo, Zhiguo Shi.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), poster, 2023
Propose point flow as a novel point clouds descriptor to explore more dynamic information for human gait. Devise a dynamic frame sampling module to promote the efficiency of computation without deteriorating performance noticeably.
Yu Fu$^{*}$, Yanyan Huang$^{*}$, Meng Niu, Le Xue, Shunjie Dong, Shunlin Guo, Junqiang Lei, Cheng Zhuo.
IEEE International Symposium on Biomedical Imaging (ISBI), poster, 2022
For the first time discussed the differences between MDD and HC using both rich club and diverse club metrics and found the complementarity of them in analyzing brain networks. Proposed “active index”, which defines a group of nodes that tend to be diversely distributed across communities while avoiding being a hub of a community.
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Yu Fu, Shunjie Dong, Yanyan Huang, Meng Niu, Chao Ni, Lequan Yu, Kuangyu Shi, Zhijun Yao, Cheng Zhuo
Medical Image Analysis (MIA), 2024
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Sex-dependent nonlinear Granger connectivity patterns of brain aging in healthy population
Yu Fu, Le Xue, Meng Niu, Yuanhang Gao, Yanyan Huang, Hong Zhang, Mei Tian, Cheng Zhuo.
Progress in Neuro-Psychopharmacology and Biological Psychiatry (PNP), 2024
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Yu Fu, Yanyan Huang, Shunjie Dong, Yalin Wang, Tianbai Yu, Meng Niu and Cheng Zhuo.
IEEE International Symposium on Biomedical Imaging (ISBI), poster, 2023
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Yu Fu, Shunjie Dong, Meng Niu, Le Xue, Hanning Guo, Yanyan Huang, Yuanfan Xu, Kuangyu Shi, Qianqian Yang, Yiyu Shi, Mei Tian, Cheng Zhuo.
Medical Image Analysis (MIA), 2023
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Yu Fu, Meng Niu, Yuanhang Gao, Shunjie Dong, Yanyan Huang, Zhe Zhang and Cheng Zhuo.
Journal of Neural Engineering (JNE), 2022
Honors and Awards
- 2023.05 Gold Medal (7/1165) in Kaggle “Google - Isolated Sign Language Recognition” Competition.
- 2022.09 Gold Medal (4/1175) in Kaggle “Hacking the Human Body” Competition.
- 2022.05 Silver Medal (Top 2%) in Kaggle “HM Recommendation” Competition.
- 2020.06 People’s Scholarship in Harbin Institute of Technology (Four consecutive years).
- 2018.10 National Scholarship in China (1.8%).
- 2018.07 The first prize of the Northeast Division of the “NXP” Cup Smart Car Competition.
- 2018.04 Meritorious Winner, Interdisciplinary Contest in Modeling (ICM), Consortium for Mathematics and Its Application.
Educations
- 2023.08 - Present, Department of Statistics and Actuarial Science, The University of Hong Kong.
- 2020.09 - 2023.03, College of Information Science and Electronic Engineering, Zhejiang University.
- 2016.09 - 2020.06, School of Electronics and Information Engineering, Harbin Institite of Technology.
Professional Activities
Journal Reviewers
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Conference Reviewers
- International Conference on Computer Vision (ICCV) 2023 CVAMD Workshop