Xiang "Shaun" Li, Ph.D.

Here is my personal homepage: xiangli-shaun.github.io

I am currently an Assistant Professor working at the Massachusetts General Hospital and Harvard Medical School, Department of Radiology. 

Research Investigation

My research focus is on the development of generalized, robust, and explainable solutions for multi-modal AI solutions in healthcare. I have published over 160 papers in top journals and conferences, including Nature Medicine, IEEE TPAMI, NeurIPS, ICLR, and ICML, with more than 13,000 citations and an h-index of 53. My research has been supported by the U.S. National Institutes of Health (NIH) and instituional grants, with focus on topics such as large language models in medicine, multimodal data fusion, and generative AI for screening support. I have received numerous honors and awards, including the Google Scholar Program Award, the Thrall Innovation Grants Award, the NVIDIA Global Impact Award, and multiple Best Paper Awards from leading journals and conferences.

Technological Innovation

At MGH, I have worked with physicians, radiologists, and system engineers to deliver novel solutions for medical data. I have one US Patent (US Patent No. 2024/0379239) for an ensemble machine-learning Aortic Stenosis Ensemble Risk Prediction (AS-ERP) model that uses EMR data to predict patient outcomes (length of stay and readmission); and another patent pending on a diffusion-based method that synthesizes 3D CT volumes from 2D radiographs, which achieved clinically acceptable validation performance through rigours human reader study. 

Service to the Community

I have been serving as the editorial boards/area chairs of several international journals and conferences, including IEEE TMI, IEEE TAI, NeurIPS, AAAI, and MICCAI. I also served as grant review panalist for several NIH study sections. To promote the importance and advancement of multi-modal, multi-scale medical image analysis and facilitate more interactions between clinical and data science experts, I founded and chaired the International Workshop on Multiscale Multimodal Medical Imaging (MMMI) in 2019, 2022, 2023, and 2024.

Teaching and Educational Activities

I am on the thesis comittee for 3 PhD. students. I have mentored 6 research fellows and 4 students. Through mentorship and co-working on research projects, most of the research fellows and students have accomplished more than one publication in scientific journals or conferences. In addition, I have given multiple lectures on AI for healthcares in internaltional conferences, workshops, seminars, and schools.