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Lyle Ungar is a Professor in the Department of Computer and Information Science at the University of Pennsylvania. He also holds professorships in Psychology and Bioengineering, and is involved in research within Operations and Information Decisions. His work spans various areas including information economics, statistical relational learning, text mining, machine learning, and computational biology. Prof. Ungar is known for his contributions to fields such as active learning, market-based methods, and distributed scheduling. His research interests also encompass gene protein expression, clustering, collaborative filtering, genomics, and information extraction. He focuses on how behavioral science and large-scale studies can inform decision making and improve outcomes. His extensive publication record includes studies on nudges for vaccination encouragement and various machine learning applications in diverse domains. Ungar is committed to advancing both theoretical frameworks and practical applications in his areas of expertise, aiming to create impactful technological solutions and promote interdisciplinary collaboration.
Wharton Doctoral programs cover fields like Finance, Marketing, Management, and Operations, Information and Decisions.