Ryan O'Donnell
My research is in the areas of quantum computation, quantum complexity theory, and quantum information. I am particularly interested in the mathematical theory of quantum tomography, as well as related problems concerning testing, certifying, and learning quantum states with low sample complexity and computational complexity. I like to apply a wide range of mathematical tools (representation theory, probability, combinatorics, Fourier analysis) when attacking problems in the theory of quantum computation and quantum information.
- "Optimal Inapproximability Results for MAX‐CUT and Other 2‐Variable CSPs?," Subhash Khot, Guy Kindler, Elchanan Mossel, and Ryan O’Donnell, SIAM J. Comput.,37, 319 (2007)
- "Analysis of Boolean Functions," Ryan O’Donnell,Cambridge University Press (2014).
- "Noise stability of functions with low influences: invariance and optimality,"Elchanan Mossel, Ryan O'Donnell, Krzysztof Oleszkiewicz, FOCS 171, 295 (2005).
- "Learning functions of k relevant variables," Elchanan Mossel, Ryan O’Donnell, and Rocco A. Servedioc, Journal of Computer and System Sciences 69, 421 (2004).
- "Learning intersections and thresholds of halfspaces," Adam R. Klivans, Ryan O’Donnell, and Rocco A. Servedio, Journal of Computer and System Sciences 68, 808 (2004).
- "Optimal mean-based algorithms for trace reconstruction." De, Anindya, Ryan O’Donnell, and Rocco A. Servedio. The Annals of Applied Probability 29, no. 2 (2019): 851-874.
- "The threshold for SDP-refutation of random regular NAE-3SAT." Deshpande, Yash, Andrea Montanari, Ryan O'Donnell, Tselil Schramm, and Subhabrata Sen. In Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 2305-2321. Society for Industrial and Applied Mathematics (2019).
- "Learning sparse mixtures of rankings from noisy information." De, Anindya, Ryan O'Donnell, and Rocco Servedio. arXiv preprint arXiv:1811.01216 (2018).
- "A log-Sobolev inequality for the multislice, with applications." Filmus, Yuval, Ryan O'Donnell, and Xinyu Wu. arXiv preprint arXiv:1809.03546 (2018).
- "SOS lower bounds with hard constraints: think global, act local." Kothari, Pravesh, Ryan O'Donnell, and Tselil Schramm. arXiv preprint arXiv:1809.01207 (2018).
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John Keith received his B.A. in Chemistry from Wesleyan University and his Ph.D. in Chemistry from California Institute of Technology. After a post doctoral position at the University of Ulm in Germany and then at Princeton, he joined the University of Pittsburgh in 2013 as a an assistant professor of Chemical and Petroleum Engineering. He also acts as the Graduate student recruiting coordinator for his department. He has received several awards, including the Alexander von Humboldt Postdoctoral Fellowship for his post doctoral appointment at Ulm, and was on the list of the Pittsburgh Business Times Who's Who in Energy in 2014.
Willian “Bill” Stanchina received his B.S.from the University of Notre Dame and his Ph.D. from the University of Southern California, both in Electrical Engineering. He then worked at HRL Laboratories (formerly Hughes Research Laboratories) for more than 20 years during which he became the Director of the Microelectronics Laboratory. There, he was directly involved in research, development, as well as low volume production. He also holds a patent. He finally joined the Department of Electrical and Computer Engineering of the University of Pittsburgh in 2005 as Professor and served as Department Chair for ten years.
Andrew Daley grew up in Auckland, New Zealand, where he completed his M.S. in Physics in 2002. He received his Ph.D. from the University of Innsbruck in 2005. He held an assistant position at the University of Innsbruck and then a senior scientist position at the Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences. In 2011 he began a faculty position at the University of Pittsburgh. He co-founded the Pittsburgh Quantum Institute in 2012 before moving to the University of Strathclyde in Scotland where he was appointed as a full professor in 2013.