BME7900 Seminar Series – Jeremias Sulam, PhD
We welcome of our first speaker of the Fall semester, Dr. Jere Sulam. Dr. Sulam is an Assistant Professor in the Department of Biomedical Engineering at Johns Hopkins University.
Imaging, Data, and Learning: Modern Challenges in Biomedical Data Science
Abstract: Modern machine learning methods have revolutionized what can be done in biomedical imaging. We can now image and reconstruct, measure, and understand biological structures from data to a degree that was hardly imaginable a decade ago. Yet, with these more powerful tools come new challenges, including uncertainty quantification, interpretability, and demographic fairness, among others. This talk will present works that illustrates these points and present some solutions to these problems, devising algorithms with provable guarantees as well as applications to real world imaging problems.
Bio: Jeremias Sulam received his bioengineering degree from Universidad Nacional de Entre Ríos, Argentina, in 2013, and his PhD in Computer Science from the Technion – Israel Institute of Technology, in 2018. He joined the Biomedical Engineering Department at Johns Hopkins University in 2018 as an assistant professor, and he is also a core faculty at the Mathematical Institute for Data Science (MINDS) and the Center for Imaging Science at JHU. He is the recipient of the Best Graduates Award of the Argentinean National Academy of Engineering, and the Early CAREER award of the National Science Foundation. His research interests include inverse problems in medical imaging, sparse representation modeling and trustworthy machine learning.
