Una-May O'Reilly

O'Reilly is a senior research scientist at the MIT Computer Science and Artificial Intelligence Laboratory, where she leads a team focusing on Artificial Adversarial Intelligence. The vision of her research group, Anyscale Learning For All (ALFA), is to computationally replicate Adversarial Intelligence. Her goal is to reveal new insights into the nature of Adversarial Intelligence and Adversarial Behavior, including questions like: How can it be used to strengthen defenses? How can it be used to anticipate what an adversary may do? How and why does it continue or cease? How does it lead to escalation? She consequently studies regulatory compliance, information security, and cyber security.^[6]

Prior ALFA research topics include intelligent data analytics and the modelling of medical data.^[2][7] O'Reilly has designed computational models for a variety of different problems, including calculating the financial risk of renewable energy investments and creating a flavor algorithm that replaces taste testers.^[8] O'Reilly has developed statistical models to inform the design of renewable energy systems, including predicting wind speed.^[9][10]

In 2013 she was awarded the EvoStar award for Outstanding Contribution to Evolutionary Computation in Europe.^[11][12] O'Reilly has received other various awards and honours for her work in genetic programming, including being elected to multiple terms serving on the executive board of the ACM Special Interest Group on Genetic and Evolutionary Computation, SIGevo^[13] (formerly International Society of Genetic and Evolutionary Computation).

• Kinnear, Kenneth E.; Langdon, William B.; Spector, Lee; Angeline, Peter J.; O'Reilly, Una-May (1994). Advances in Genetic Programming. MIT Press. ISBN 978-0-262-19423-5.
• Ansel, Jason; Kamil, Shoaib; Veeramachaneni, Kalyan; Ragan-Kelley, Jonathan; Bosboom, Jeffrey; O'Reilly, Una-May; Amarasinghe, Saman (2014). "OpenTuner". Proceedings of the 23rd international conference on Parallel architectures and compilation. New York, New York, USA: ACM Press. pp. 303–316. doi:10.1145/2628071.2628092. ISBN 978-1-4503-2809-8.
• Poli, Riccardo, 1961- (2008). A field guide to genetic programming. Langdon, W. B. (William B.), McPhee, Nicholas F., Koza, John R. [S.I.]: [Lulu Press], lulu.com. ISBN 978-1-4092-0073-4. OCLC 225855345.{{cite book}}: CS1 maint: multiple names: authors list (link) CS1 maint: numeric names: authors list (link)
• Stephenson, Mark; Amarasinghe, Saman; Martin, Martin; O'Reilly, Una-May (2003-05-09). "Meta optimization: improving compiler heuristics with machine learning". ACM SIGPLAN Notices. 38 (5): 77–90. doi:10.1145/780822.781141. ISSN 0362-1340.