Nihar B. Shah is an assistant professor in the Machine Learning and Computer Science Departments at Carnegie Mellon University (CMU). His research interests span statistics, machine learning, information theory, and game theory. His recent work focuses on improving the peer-review process by designing computational methods, mathematical guarantees, experimental evaluations and deployments, and has had significant real-world impact.

In addition to his professorship, Shah was the associate program chair of the Association for the Advancement of Artificial Intelligence conference, the acting editor for Transactions on Machine Learning Research, and has served as a committee member for numerous conferences. Shah’s work is well recognized and has received a number of awards, including the JP Morgan Faculty Research Award, the Google Research Scholar Award, the NSF CAREER Award, and several best paper awards, among others.

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CyLab Security and Privacy Institute

First round of Future Enterprise Security Initiative funded projects announced

CyLab’s Future Enterprise Security Initiative is underway as the first round of funded proposals has been announced.