😊About Me

I am a PhD student at the University of Science and Technology of China (USTC) supervised by Prof. S. Kevin Zhou. I focus on self-supervised learning, foundation model, medical image analysis, computer vision and pattern recognition. I received my bachelor’s and master’s degrees from Harbin Institute of Technology (HIT) in 2021 and 2023, respectively. My master’s tutor is Prof. Jianrui Ding. I have published 20+ papers at top conferences and journals with citations
Hobbies: 🎞️🏀🀄🃏🍔

🔥 News

Find collaborators on foundation model & medical image segmentation, feel free to contact me at fhtan9@mail.ustc.edu.cn 😎🥰🤗🤗🤗

2025.07: One paper accepted to ACM MM-25.
2025.06: Three papers accepted to MICCAI-25.
2025.04: One paper accepted to npj Digital Medicine.
2025.04: One paper accepted to Nature Communications.
2025.04: One paper accepted to Medical Image Analysis.
2025.03: One paper accepted to MIDL-25.
2025.03: One paper accepted to CVPR-25.
2024.06: One paper accepted to MICCAI-24.
2024.05: One paper accepted to MICCAI-24 (Early Accept, Top 11 %).
2024.04: One paper accepted to MIDL-24 (Oral, Best Oral Paper Finalists).
2024.02: One paper accepted to ISBI-24 (Oral).

MambaMIM: Pre-training Mamba with State Space Token-interpolation and its Application to Medical Image Segmentation

Fenghe Tang*, Bingkun Nian*, Yingtai Li*, Jie Yang, Wei Liu, S. Kevin Zhou. [paper] [code]
Hi-End-MAE: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentation

Fenghe Tang, Qingsong yao, Wenxin Ma, Chenxu Wu, Zihang Jiang, S. Kevin Zhou. [paper] [code]
HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training (Early Accept)

Fenghe Tang, Ronghao Xu, Qingsong Yao, Xueming Fu, Heqin Zhu, Zaiyi Liu, S. Kevin Zhou. [pape] [code]
Slide-SAM: Medical SAM Meets Sliding Window (Oral, Best Oral Paper Finalists)

Quan Quan*, Fenghe Tang*, Zikang Xu, Heqin Zhu, S. Kevin Zhou. [paper] [code]

Mobile U-ViT: Revisiting large kernel and U-shaped ViT for efficient medical image segmentation

Fenghe Tang, Bingkun Nian, Jianrui Ding, Wenxin Ma, Quan Quan, Chengqi Dong, Jie Yang, Wei Liu, S. Kevin Zhou.
Pre-Trained LLM is a Semantic-Aware and Generalizable Segmentation Booster

Fenghe Tang, Wenxin Ma, Zhiyang He, Xiaodong Tao, Zihang Jiang, S. Kevin Zhou. [paper] [code]
CMUNeXt: An Efficient Medical Image Segmentation Network based on Large Kernel and Skip Fusion (Oral)

Fenghe Tang, ‪Jianrui Ding‬‬, Quan Quan, Lingtao Wang, Chunping Ning,‪ S. Kevin Zhou‬‬. [paper] [code]
CMU-Net: A Strong ConvMixer-based Medical Ultrasound Image Segmentation Network

Fenghe Tang, Lingtao Wang, Chunping Ning, Min Xian, Jianrui Ding. [paper] [code]
Fair ultrasound diagnosis via adversarial protected attribute aware perturbations on latent embeddings

Zikang Xu, Fenghe Tang, Quan Quan, Qingsong Yao, Qingpeng Kong, Jianrui Ding, Chunping Ning, S. Kevin Zhou. [paper] [code]

Deep generalizable prediction of RNA secondary structure via base pair motif energy

Heqin Zhu, Fenghe Tang, Quan Quan, Ke Chen, Peng Xiong, S. Kevin Zhou. [paper] [code]

More publications are available at: Google Scholar

Suzhou Industrial Park Scholarship, University of Science and Technology of China, 2024
Outstanding Master’s Theses, Harbin Institute of Technology, 2023
National Scholarship for Postgraduates, Chinese Ministry of Education, 2023
Outstanding Graduate Reward, Harbin Institute of Technology, 2023
Excellent Developer of Mindspore , HUAWEI, 2022
Outstanding Graduate Reward, Shandong Province, 2021
The Grand Prize of CANN, HUAWEI, 2021

2023.09 - (now), Ph.D of Electronic Information, School of BME, University of Science and Technology of China.
2021.09 - 2023.06, Master of Computer Technology, School of Computer Science and Technology, Harbin Institute of Technology.
2017.09 - 2021.06, Bachelor of Software Engineering, School of Computer Science and Technology, Harbin Institute of Technology.

Conference Reviewers:

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025
ACM International Conference on Multimedia (ACM MM), 2025
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024-2025

Teaching Assistant: