Hi! I’m Zihan, a first-year Ph.D. student at University of Washington, Seattle, advised by Prof. Paul Kinahan (IEEE Life Fellow, FAAPM, FSNMMI, FAIMBE). And I received my Master degree from the Department of Computer Science, UIUC in 2023.
My research focuses on Large Multimodal Model (LMM) including vision-language model, self-supervised learning, and medical image analysis. I am committed to helping doctors or researchers carry out quantitative analysis and treatment planning for tissues and organs of the human body by combining deep learning with medical images.
- 🔥 [Aug 2023] Our work ScribbleVC is accepted by ACM MM 2023.
- 🔥 [July 2023] One papers is accepted by ICCV 2023.
- 🔥 [June 2023] Our work LViT is accepted by IEEE Transactions on Medical Imaging (TMI).
- 🔥 [May 2023] We release the first Medical LLM ChatDoctor and its huggingface repo.
- 🔥 [May 2023] Two papers (SwinMM, CorSegRec) are accepted by MICCAI 2023 as Oral Presentation.
- [May 2023] One paper is accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
- [May 2023] Awarded the Conference Presentation Award for Graduate Students by UIUC!
- [February 2023] Our Work C2FVL is accepted by ICASSP 2023.
My work and research
My current works focus on the multimodal learning, including natural language and radiology reports. At the same time, I pay attention to the corner case datasets to alleviate AI for Underrepresentation in medical field. I have participated in multiple internships in both academia and industry. I have worked as a research intern at the University of Cambridge, Johns Hopkins University and Peking University, as well as at Alibaba DAMO Academy and Shanghai AI Laboratory. Several respected professors have guided my research, including Prof. Alan L. Yuille, Prof. Pietro Liò, Prof. Dinggang Shen, Prof. Jie Tian, Prof. Yu Qiao, Dr. Le Lu, and I have collaborated with them on many works.