Varatharajah is broadly interested in leveraging the recent advances in machine learning (ML) to improve the healthcare system. For his research studies, he works very closely with clinical experts to develop novel domain-guided ML applications that reduce physician burden, augment their capabilities, and enhance the overall patient experience while ensuring reliability, scalability, and trust. The ML topics he focuses on are domain-guided ML, self-supervised learning, generative modeling, trustworthy ML, robustness, and ML safety. A particular focus area of his work has been on improving the treatments for neurological diseases, where he developed novel graph-based ML methods to model brain activity patterns in diseases such as Alzheimer's and epilepsy. 

Research Division
Data Science and Machine Learning

Current Research
Google Scholar
Health Intelligence Lab

Education

Ph.D. in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (2020) 
M.S. in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (2015) 
B.S. in Electronic and Telecommunication Engineering, University of Moratuwa (2013)

Professional Background

Yogatheesan Varatharajah joined the Department of Computer Science & Engineering in fall 2023 as an assistant professor. He earned him M.S. (2015) and Ph.D. (2020) in electrical and computer engineering from the University of Illinois at Urbana-Champaign. In additional to his work with the Department, Varatharajah is a visiting scientist in the Department of Neurology at the Mayo Clinic. Prior to joining the University of Minnesota, he was a research assistant professor of bioengineering at the University of Illinois, as well as a faculty affiliate for the Center for Artificial Intelligence Innovation with the National Center for Supercomputing Applications.

Teaching Subjects

• Machine Learning for Health
• Trustworthy Machine Learning
• Computational Mathematics