Una-May O'Reilly explained

Una-May O'Reilly
Alma Mater:	University of Calgary Carleton University
Workplaces:	Massachusetts Institute of Technology
Thesis Title:	An analysis of genetic programming
Thesis Url:	http://www.worldcat.org/oclc/46500563
Thesis Year:	1996
Awards:	EvoStar Award for Outstanding Contribution to Evolutionary Computation

Una-May O'Reilly is a Canadian computer scientist and leader of the Anyscale Learning For All (ALFA) group at the MIT Computer Science and Artificial Intelligence Laboratory.

Early life and education

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

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.^[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

• Book: Kinnear. Kenneth E.. Advances in Genetic Programming. Langdon. William B.. Spector. Lee. Angeline. Peter J.. O'Reilly. Una-May. 1994. MIT Press. 978-0-262-19423-5. en.
• Book: Ansel. Jason. Kamil. Shoaib. Veeramachaneni. Kalyan. Ragan-Kelley. Jonathan. Bosboom. Jeffrey. O'Reilly. Una-May. Amarasinghe. Saman. Proceedings of the 23rd international conference on Parallel architectures and compilation . OpenTuner . 2014. 303–316. New York, New York, USA. ACM Press. 10.1145/2628071.2628092. 978-1-4503-2809-8. free.
• Book: Poli, Riccardo, 1961-. A field guide to genetic programming. 2008. [Lulu Press], lulu.com. Langdon, W. B. (William B.), McPhee, Nicholas F., Koza, John R.. 978-1-4092-0073-4. [S.I.]. 225855345.
• 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. 10.1145/780822.781141. 0362-1340.

References

1. Web site: Una-May O'Reilly. 2020-09-12. MIT-IBM Watson AI Lab. en.
2. Web site: Dr Una-May O'Reilly. 2020-09-12. Crossword Cybersecurity.
3. Web site: Imperial and MIT explore how our future could be shaped by AI Imperial News Imperial College London. 2020-09-12. Imperial News. 5 March 2018 . en.
4. Web site: STEMM CSAIL AI in Healthcare Summit. 2020-09-12. Stemm.ai. en-US.
5. Web site: foodnavigator-usa.com. Givaudan to work with MIT researchers on 'flavor algorithms'. 2020-09-12. foodnavigator-usa.com. 31 January 2012 . en-GB.
6. Web site: Siting wind farms more quickly, cheaply. 2020-09-12. MIT News Massachusetts Institute of Technology. 17 July 2015 . en.
7. Web site: Calculating the financial risks of renewable energy. 2020-09-12. MIT News Massachusetts Institute of Technology. 15 September 2016 . en.
8. Web site: Compatibility. 2020-09-12. app.livestorm.co.
9. Web site: Evostar 2019 - Leipzig. 2020-09-12. www.evostar.org.