Lyle H. Ungar

Computer and Information Science (CIS)

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Honors and Awards:  NSF Presidential Young Investigator Award

Research Expertise: Machine Learning | Bioinformatics

Lyle develops machine learning and text mining methods in order to solve problems in genomics, bioinformatics, and information extraction. Key to his work in building scalable solutions to such problems is the development of methods that can exploit knowledge, including the link structure between documents or genes and the structure of the relational database training from which data are drawn. Lyle and his group are also developing theoretically grounded feature selection methods that scale to millions of features, and scalable clustering and regression algorithms.

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Affiliations:  Associate Professor of Operations and Information Management (Wharton); Associate Professor of Genomics and Computational Biology (SOM)

PhD 1984 - Massachusetts Institute of Technology
BS 1979 - Stanford University

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