Stephen Ramsey, Associate Professor
Biomedical Sciences and Electrical Engineering and Computer Science
I will describe our work on two projects: an NIH consortium project, the Biomedical Data Translator, and a project to use machine learning to improve outcomes in cancer treatment. The Biomedical Data Translator project's broad aim is to advance translational science using computer-aided knowledge exploration and reasoning. Our team is developing a reasoning system, ARAX, that is geared toward drug repositioning for common diseases and therapeutic recommendation for rare inherited diseases. I will describe some of the principles behind this system and key challenges inherent to building scalable reasoning systems. For the precision oncology project, I will also present some recent work in our lab on using machine-learning to predict response to chemotherapy based on transcriptome data acquired from tumor samples.
ABOUT THE PRESENTER
Stephen originally trained in physics and mathematics, earning an ScB from Brown University and a PhD from the University of Maryland. Building on his computational modeling experience, Stephen trained as a postdoc at the University of Washington Genome Center, where he worked on the Human Genome Project in Maynard Olson's laboratory. Stephen's work on genome mapping algorithms paved the way toward molecular-oriented research projects in the labs of Hamid Bolouri and Ilya Shmulevich at the Institute for Systems Biology. As a senior scientist in Alan Aderem's laboratory at the Center for Infectious Disease Research, Stephen worked on computational methods for mapping gene regulatory networks. At OSU, Stephen holds a dual appointment in the Department of Biomedical Sciences and in the School of Electrical Engineering and Computer Science. Stephen's research has been recognized by multiple awards including an NIH K25 Career Development Award, a PhRMA New Investigator Award, an NSF CAREER award, and the Carlson College of Veterinary Medicine Zoetis Award.
Lab website: https://lab.saramsey.org/
Zoom ID: 987 6966 9284
Monday, January 4 at 4:00pm to 4:50pmVirtual Event