Shuo Li, PhD

Professor
Biomedical Engineering
Case School of Engineering
School of Medicine
Professor
Department of Computer and Data Sciences
Case School of Engineering
Member
Cancer Imaging Program
Case Comprehensive Cancer Center

Dr. Li is a global leader in conducting multi-disciplinary research to enable artificial intelligence (AI) in clinical imaging. He is an academic AI scientist with a background in machine learning, medical data analytics, and imaging. His current research focuses on the development of image-centered AI systems. These systems are designed to solve the most challenging clinical and fundamental data analytics problems in various fields, including cardiology, radiology, urology, surgery, rehabilitation, and cancer. He emphasizes innovations in multiple learning schemes such as deep, regression, reinforcement, adversarial, sparse, spectral, and manifold learning. Dr. Li serves as a committee member for multiple highly influential conferences and societies. He is most notable for his role on the prestigious board of directors of the MICCAI Society, a position he held from 2015 to 2024, and as the general chair of the MICCAI 2022 conference. With over 200 publications, Dr. Li has also acted as the editor for six Springer books and is an associate editor for several prestigious journals. He has received numerous awards from GE, various institutes, and international organizations throughout his career.

Research Information

Research Interests

Dr. Li is a global leader in conducting multi-disciplinary research to enable artificial intelligence (AI) in clinical imaging. He is an academic AI scientist with a background in machine learning, medical data analytics, and imaging. His current research focuses on the development of image-centered AI systems. These systems are designed to solve the most challenging clinical and fundamental data analytics problems in various fields, including cardiology, radiology, urology, surgery, rehabilitation, and cancer. He emphasizes innovations in multiple learning schemes such as deep, regression, reinforcement, adversarial, sparse, spectral, and manifold learning. Dr. Li serves as a committee member for multiple highly influential conferences and societies. He is most notable for his role on the prestigious board of directors of the MICCAI Society, a position he held from 2015 to 2024, and as the general chair of the MICCAI 2022 conference. With over 200 publications, Dr. Li has also acted as the editor for six Springer books and is an associate editor for several prestigious journals. He has received numerous awards from GE, various institutes, and international organizations throughout his career.

Learn more about Shuo Li

Awards and Honors

MICCAI Elsevier MedIA MICCAI 2022 Special Issue Best Paper Award, Runner Up
International Conference on Artificial Intelligence 2021 Best Student Paper
MICCAI Young Scientist Award
2017
Annual Award for Academic Excellence in Research
2017
Department of Medical Imaging, Western University
Above & Beyond Award
2014
General Electric
GE Innovation Award
2009
General Electric
GE Management Award
2008
General Electric
GE Hero Award
2008
General Electric
Doctoral Prize – Distinction
2007
Concordia University

Publications

  • Towards Accurate and Robust Domain Adaptation Under Multiple Noisy Environments. Z Han, X Gui, H Sun, Y Yin, S Li. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
  • United Adversarial Learning for Liver Tumor Segmentation and Detection of Multi-modality Non-contrast MRI. J Zhao, D Li, X Xiao, F Accorsi, H Marshall, T Cossetto, D Kim, ... Medical Image Analysis 73, 102154, 2022
  • Evaluation and Comparison of Accurate Automated Spinal Curvature Estimation Algorithms with Spinal Anterior-posterior X-Ray Images: The AASCE2019 Challenge. L Wang, C Xie, Y Lin, HY Zhou, K Chen, D Cheng, F Dubost, B Collery, ... Medical Image Analysis, 2022

View ful list of publications