Nihar Shah, an assistant professor in the School of Computer Science's Machine Learning and Computer Science Departments, has received a National Science Foundation Faculty Early Career Development (CAREER) Award, the organization's most prestigious award for young faculty members. The five-year, $648,000 award will support his work to improve the fairness of peer-review systems and address issues such as biases and dishonest behavior.
Shah's research specialties include machine learning, game theory and crowdsourcing. With the NSF grant, he will design new algorithms for eliciting data from people and processing it in a manner that mitigates biases and unfairness to the greatest possible extent. The research will have a particular focus on peer review of scholarly research, with a wide variety of other applications including hiring, college admissions, recommender systems and crowdsourcing.
The project will employ tools from machine learning, statistics, information theory, game theory and social choice. Shah will also release open-source toolkits for practitioners and employ outreach efforts towards creating positive policy change.
Shah received his Ph.D. in electrical engineering and computer science from the University of California Berkley in 2017, where his thesis earned the David J. Sakrison Memorial Prize for a "truly outstanding piece of research."
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