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Ryan O'Donnell is a Professor in the Computer Science Department at Carnegie Mellon University. His research focuses on a variety of topics within theoretical computer science, including algorithms, complexity, and learning theory. He has an extensive background in Fourier analysis and its applications to Boolean functions, as well as in constraint satisfaction problems and quantum computation. O'Donnell is highly regarded for his work on the inapproximability of random instances and proof complexity. His contributions to probability theory and property testing have also significantly advanced the field. In addition to his academic research, he is actively involved in teaching, offering courses on various subjects, including advanced algorithms and computational complexity. His academic work has led to numerous publications in prestigious journals and conferences, reflecting his expertise and influence in the field.
Admission is extremely competitive with no strict GPA cut-offs; holistic review is used.