AI4Medicine is not Just Vanilla and Chocolate: Its at least Baskin-Robbins!
Abstract
Data-driven methods are dominating the recent developments in artificial intelligence. When applied to medicine many challenges remain die to domain shift, lack of annotations, the needed amount of data, potential bias, etc. In this talk, I will discuss our current works on applying AI methodologies for multiple conditions drawn from eye care, cancer, pathology, geriatrics, autism, and stroke and how we address some of the challenges mentioned above.
Bio
Rama Chellappa
Bloomberg Distinguished Professor
Prof. Rama Chellappa is a Bloomberg Distinguished Professor in the Departments of Electrical and Computer Engineering and Biomedical Engineering at Johns Hopkins University (JHU). At JHU, he is also affiliated with CIS, CLSP, IAA, and MINDS. He holds a non-tenured position as a College Park Professor in the ECE department at UMD. His researcher interests are in computer vision, pattern recognition, machine learning and artificial intelligence. He received the 2012 K. S. Fu Prize from the International Association of Pattern Recognition (IAPR). He is a recipient of the Society, Technical Achievement, and Meritorious Service Awards from the IEEE Signal Processing Society, the Technical Achievement and Meritorious Service Awards from the IEEE Computer Society and the Inaugural Leadership Award from the IEEE Biometrics Council. He received the 2020 IEEE Jack S. Kilby Medal for Signal Processing. He is an elected member of the National Academy of Engineering. He is a Fellow of AAAI, AAAS, ACM, AIMBE, IAPR, IEEE, NAI, OSA, and the Washington Academy of Sciences and holds nine patents.