Una-May O'Reilly is an American computer scientist and leader of the Anyscale Learning For All (ALFA) group at the MIT Computer Science and Artificial Intelligence Laboratory.
Una-May O'Reilly | |
|---|---|
 | |
| Alma mater | University of Calgary Carleton University |
| Awards | EvoStar Award for Outstanding Contribution to Evolutionary Computation |
| Scientific career | |
| Institutions | Massachusetts Institute of Technology |
| Thesis | An analysis of genetic programming (1996) |
Early life and education edit
O'Reilly earned her undergraduate degree at the University of Calgary. She was a graduate student at the Carleton University, where she studied computer science. During her doctorate O'Reilly worked as a graduate fellow at the Santa Fe Institute. Her dissertation was one of the first to explore genetic programming.[1] She joined the MIT Computer Science and Artificial Intelligence Laboratory as a postdoctoral fellow in 1996.[2]
Research and career edit
O'Reilly is a principal research scientist at the MIT Computer Science and Artificial Intelligence Laboratory, where she leads a team focusing on scalable machine learning. Her research group, Anyscale Learning For All (ALFA), conducts research in cybersecurity,[3] rapid intelligent data analytics and the modelling of medical data.[1][4] 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.[5] O'Reilly has developed statistical models to inform the design of renewable energy systems, including predicting wind speed.[6][7]
In 2013 she was awarded the EvoStar award for Outstanding Contribution to Evolutionary Computation in Europe.[8][9] O'Reilly has received various awards and honours for her work in genetic programming; including being elected to the Executive Board of the ACM Special Interest Group on Genetic and Evolutionary Computation, SIGevo (formerly International Society of Genetic and Evolutionary Computation).
Select publications edit
- 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.
References edit
- ^ a b "Una-May O'Reilly". MIT-IBM Watson AI Lab. Retrieved 2020-09-12.
- ^ "Dr Una-May O'Reilly". Crossword Cybersecurity. Retrieved 2020-09-12.
- ^ "Imperial and MIT explore how our future could be shaped by AI | Imperial News | Imperial College London". Imperial News. 5 March 2018. Retrieved 2020-09-12.
- ^ "STEMM CSAIL AI in Healthcare Summit". Stemm.ai. Retrieved 2020-09-12.
- ^ foodnavigator-usa.com (31 January 2012). "Givaudan to work with MIT researchers on 'flavor algorithms'". foodnavigator-usa.com. Retrieved 2020-09-12.
- ^ "Siting wind farms more quickly, cheaply". MIT News | Massachusetts Institute of Technology. 17 July 2015. Retrieved 2020-09-12.
- ^ "Calculating the financial risks of renewable energy". MIT News | Massachusetts Institute of Technology. 15 September 2016. Retrieved 2020-09-12.
- ^ "Compatibility". app.livestorm.co. Retrieved 2020-09-12.
- ^ "Evostar 2019 - Leipzig". www.evostar.org. Retrieved 2020-09-12.