Scholar
Yunhe Gao
Google Scholar ID: TOsFPu4AAAAJ
Stanford University, Rutgers University
Citations & Impact
Citations
1,745
H-index
15
i10-index
17
Publications
20
Co-authors
4
list available
Publications
Resume (English only)
Academic Achievements
- - Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification, Yunhe Gao, Difei Gu, Mu Zhou, Dimitris Metaxas, MICCAI 2024, Early Accept
- - Training Like a Medical Resident: Universal Medical Image Segmentation via Context Prior Learning, Yunhe Gao, Zhuowei Li, Di Liu, Mu Zhou, Shaoting Zhang, Dimitris N. Metaxas, CVPR 2024
- - LEPARD: Learning Explicit Part Discovery for 3D Articulated Shape Reconstruction, Di Liu, Anastasis Stathopoulos, Qilong Zhangli, Yunhe Gao, Dimitris N. Metaxas, NeurIPS 2023
- - Visual prompt tuning for test-time domain adaptation, Yunhe Gao, Xingjian Shi, Yi Zhu, Hao Wang, Zhiqiang Tang, Xiong Zhou, Mu Li, Dimitris N. Metaxas, Tech Report
- - Region proposal rectification towards robust instance segmentation of biological images, Qilong Zhangli, Jingru Yi, Di Liu, Xiaoxiao He, Zhaoyang Xia, Qi Chang, Ligong Han, Yunhe Gao, Song Wen, Haiming Tang, He Wang, Mu Zhou, Dimitris Metaxas, MICCAI 2022, Early Accept
- - Transfusion: multi-view divergent fusion for medical image segmentation with transformers, Di Liu, Yunhe Gao, Qilong Zhangli, Ligong Han, Xiaoxiao He, Zhaoyang Xia, Song Wen, Qi Chang, Zhennan Yan, Mu Zhou, Dimitris Metaxas, MICCAI 2022
Research Experience
- - Feb. 2024 - Present: Could + AI, Microsoft, Remote, Part-time Research Scientist Intern, working on medical imaging foundation models
- - Jun. 2023 - Sep. 2023: Deep Engine Science, AWS, Santa Clara, CA, USA, Applied Scientist Intern, hosted by Dr. Boran Han and Dr. Zhiqiang Tang, working on large-scale dataset distillation via purified pretraining model
- - June 2022 - Sep. 2022: Deep Engine Science, AWS, Santa Clara, CA, USA, Applied Scientist Intern, hosted by Dr. Xingjian Shi and Dr. Yi Zhu, working on data-efficient test-time domain adaptation via visual prompt tuning
- - Sept. 2019 - Present: Computer Science Department, Rutgers University, Piscataway, NJ, USA, Research Assistant, supervised by Prof. Dimitris N. Metaxas, working on knowledge-driven models for explainable diagnosis, foundation medical image segmentation models, etc.
Education
- - Sept. 2019 - Present: Rutgers, The State University of New Jersey, Piscataway, NJ, Ph.D. in Computer Science, supervised by Distinguished Prof. Dimitris N. Metaxas
- - Sept. 2017 - Nov. 2018: The Chinese University of Hong Kong, Central Ave, Hong Kong, M.S. in Electronic Engineering, supervised by Prof. Hongsheng Li
- - Sept. 2013 - Jul. 2017: University of Science and Technology of China, Hefei, China, B.Eng. in Automation
Background
- Currently a PhD candidate in the Computer Science Department of Rutgers University, advised by Distinguished Professor Dimitris N. Metaxas. Research interests include: (1) medical imaging foundation models (e.g., universal medical image understanding, multimodal models); (2) Knowledge-driven models and explainable AI (e.g., injecting human prior knowledge into models, making the AI decision-making process human-understandable); (3) Model adaptability (e.g., domain adaptation, generalization, in-context learning).
