Nitesh Chawla, PhD
Visiting Research Fellow, Applied Data Sciences Center
Interim Director of the Applied Data Sciences Core
Frank M. Freimann Professor of Computer Science and Engineering, University of Notre Dame
Nitesh Chawla, PhD, is a Visiting Fellow of the Institute and the Interim Director of the Applied Data Sciences Core. He is the Frank M. Freimann Professor of Computer Science and Engineering at the University of Notre Dame and serves as director of both the iCeNSA research center on network and data sciences and the Data Inference Analytics and Learning Lab (DIAL). An accomplished academic, he has brought more than $19.5M dollars in research funding, published more than 185 papers with over 10,800 citations, and was twice awarded Notre Dame Computer Science and Engineering’s Outstanding Teaching Award.
Dr. Chawla’s innovative research on data science, machine learning, and network science has led to transformative interdisciplinary applications in healthcare, life sciences, environmental and climate sciences, education, business, and national security. He is the recipient of the IBM Watson Faculty Award, the IBM Big Data and Analytics Faculty Award, IEEE Computational Intelligence Society Outstanding Early Career Award, and the National Academy of Engineering New Faculty Fellowship. Dr. Chawla understands the entrepreneurial nature of the IBRI, having founded his own data science software company, Aunalytics, which helps others harness the power of data to fuel their economic engines.
Dr. Chawla is passionate about driving technological innovations for the common good. In recognition of the societal and community driven impact of his research, he was recognized with the Rodney F. Ganey Award and Michiana 40 Under 40. He is a Fellow of the Reilly Center for Science, Technology, and Values; Fellow of the Institute of Asia and Asian Studies; and Fellow of the Kroc Institute for International Peace Studies at Notre Dame.
Applied Data Sciences Center
Focusing on the creation of tools and development of applications that will enable deep computer learning to assist researchers, clinicians, and patients.