Stefani Karp, a Ph.D. student in the School of Computer Science's Machine Learning Department, has been awarded with the 2021 Alan J. Perlis Graduate Student Teaching Award. This award goes to the most outstanding graduate teaching assistant in the School of Computer Science. 

The SCS student teaching awards were launched in 2005 and are named after Alan J. Perlis, a founder of the Computer Science Department (CSD) at Carnegie Mellon and CSD's first Department Head (1965). These awards are based on student nominations, recommendation letters, reviews, and honors (graduate or undergraduate) who have shown the highest degree of excellence and dedication as a teaching assistant.

Machine learning students enroll for many different reasons: Some want to develop a deep understanding of a field in which they are conducting research. Others are interested in machine learning applications to real-world problems, and they know that this application requires an understanding of both relevant theory and practical knowledge. 

Professor Aarti Singh, and Karp's advisor, writes: "Stefani has been an above-and-beyond TA, mentoring students as well as fellow TAs by putting herself in their shoes, providing constructive feedback to instructors, and has been an excellent role model who sets an extremely high bar among Ph.D. students." Karp's research interests span a broad range of topics in theoretical machine learning (ML). Her work has thus far focused primarily on deriving performance guarantees in practical ML settings, with a focus on deep learning theory.

Before coming to CMU, Karp graduated from Princeton University in 2015, where she studied theoretical computer science, and her thesis focused on persistent data structures. Subsequently, she spent three years as a software engineer at Google working on search quality.

For More Information
Aaron Aupperlee | 412-268-9068 | aaupperlee@cmu.edu