Una-May O'Reilly

Una-May O'Reilly


Una-May is leader of the AnyScale Learning For All (ALFA) group at CSAIL. ALFA focuses on scalable machine learning, evolutionary algorithms, and frameworks for large scale knowledge mining, prediction and analytics.  The group has projects in clinical medicine knowledge discovery: arterial blood pressure forecasting and pattern recognition, diuretics in the ICU; wind energy: turbine layout optimization, resource prediction, cable layout; and MOOC Technology: MoocDB, student persistence and resource usage analysis.

Una-May was awarded the EvoStar Award for Outstanding Contribution of Evolutionary Computation in Europe in April, 2013. She is also is a Jr Fellow of the International Society of Genetic and Evolutionary Computation, now ACM Sig-EVO (Jr implies elected before age of 35). 

Una-May was a co-founder of ACM SigEVO in 2004. She now serves as Vice-Chair of ACM SigEVO. In 2013 she inaugurated the Women in Evolutionary Computation group at GECCO.

Una-May served as chair of the largest international Evolutionary Computation Conference,  GECCO, in 2005.  She has served on the GECCO business committee, co-led the 2006 and 2009 Genetic Programming: Theory to Practice Workshops and co-chaired EuroGP, the largest conference devoted to Genetic Programming.

Una-May serves as the area editor for Data Analytics and Knowledge Discovery for Genetic Programming and Evolvable Machines (Kluwer), as editor for Evolutionary Computation (MIT Press), and as action editor for the Journal of Machine Learning Research.

Una-May has a patent  for a original genetic algorithm technique applicable to internet-based name suggestions.

Una-May holds a B.Sc. from the University of Calgary, and a M.C.S. and Ph.D. (1995) from Carleton University, Ottawa, Canada. She joined the Artificial Intelligence Laboratory, MIT as a Post-Doctoral Associate in 1996.

Tag Cloud for Una-May O'Reilly

    "cloud computing", "big data", "data analytics", "machine learning", "evolutionary algorithms", "optimization", "stochastic optimization", "adaptive computation", "genetic algorithms", "genetic programming", "evolutionary computation","multicore optimization", "sensory science", "MIMIC II data analysis"


  • International Association for Artificial Intelligence and Law: The Peter Jackson Best Innovative Application Paper Award (2015)
  • Genetic and Evolutionary Computation Conference: Best Paper Genetic Programming track (2014)
  • EvoSTAR: Outstanding Achievements in Evolutionary Computation in Europe (2013)
  • EvoSTAR: EvoPAR Conference, Best Paper (2012)
  • International Society of Genetic and Evolutionary Computation: Fellow (2004)
  • Genetic and Evolutionary Computation Conference: "Best Paper in Track: ""An Interactive Artificial Ant Approach to Non Photorealistic Rendering"" by Y. Semet, U.M. O’Reilly, F. Durand." (2004)