Co-Lead, Model and Data Sharing Core, MISM
Director, RENCI, UNC
Ashok Krishnamurthy, PhD, MS, Core, Co-Lead, is the Director of the Renaissance Computing Institute (RENCI), a Research Professor of Computer Science at UNC-Chapel Hill, and the Co-director for Informatics and Data Science at NC TraCS. He holds a PhD and a master’s degree in electrical and computer engineering from the University of Florida and a bachelor’s degree in electrical engineering from the Indian Institute of Technology. Prior to joining RENCI and UNC in 2013, Dr. Krishnamurthy spent many years at the Ohio Supercomputer Center (OSC) and was a faculty member at The Ohio State University. While at OSC, he played a crucial role in establishing its successful industrial outreach initiative, Blue Collar Computing. Dr. Krishnamurthy also helped develop and deploy cyberinfrastructure that allows researchers to easily access and use computing and storage resources at OSC. He has many years of experience with informatics and data science, including data science cyberinfrastructure, medical image analysis, time-series data analysis, machine learning, and high-performance computing.
Dr. Krishnamurthy has over 15 years of experience as both a researcher and an administrator in advancing cutting-edge research in interdisciplinary teams. He collaborates with researchers in informatics, biomedical and health research, and the social sciences to develop projects and programs that leverage data science and scalable computing to solve challenging problems and advance the state of the art. Dr. Krishnamurthy advises undergraduate and graduate students and mentors post-doctoral scholars and junior investigators. He is also involved in managing and enhancing research partnerships with faculty at UNC-Chapel Hill, Duke University, and North Carolina State University, as well as building relationships between RENCI and Triangle-area businesses. Dr. Krishnamurthy’s research over the years has been funded by NSF, NIH, DoD, DARPA, and DOE. He is responsible for the administrative and scientific aspects of the MISM Model and Data Sharing Core.