Seminar Series: Dr. Sriraam Natarajan
April 21 @ 2:00 pm – 3:00 pm
Dr. Sriraam Natarajan is a Professor and the Director of the Center for ML at the Department of Computer Science at the University of Texas, Dallas. His research interests include Artificial Intelligence, with an emphasis on Machine Learning, Statistical Relational Learning and AI, Reinforcement Learning, Graphical Models, and Biomedical Applications. He has won several awards, including the President’s Teaching Award for excellence in graduate teaching, the Young Investigator award from the US Army Research Office, several industry awards, and best paper awards. He was the program co-chair of the AAAI 2024, SDM 2020, and ACM CoDS-COMAD 2020 conferences.
Location: Blocker 220 and Zoom
Zoom ID: 974 9688 4861
Passcode: 923446
AI: In the Loop for Healthcare
Historically, Artificial Intelligence has taken a symbolic route for representing and reasoning about objects at a higher level or a statistical route for learning complex models from large data. To achieve true AI in complex domains such as healthcare, it is necessary to make these different paths meet and enable seamless human interaction. First, I will introduce learning from rich, structured, complex, and noisy data. One of the key attractive properties of the learned models is that they use a rich representation for modeling the domain that potentially allows for seamless human interaction. I will present the recent progress that allows for more reasonable human interaction where the human input is taken as “advice”, and the learning algorithm combines this advice with data. I will present these algorithms in the context of several healthcare problems- learning from electronic health records, clinical studies, and surveys- and demonstrate the value of involving experts during learning.