` Una-May O'Reilly's Webpage
Una-May O'Reilly, Ph.D.
Principal Research Scientist
email: unamay "at" csail dot mit dot edu
office: D534 Stata Center, MIT


Una-May O'Reilly leads the AnyScale Learning For All (ALFA) group. She has expertise in scalable machine learning, evolutionary algorithms, and frameworks for large-scale, automated knowledge mining, prediction and analytics. She educates the forthcoming generation of data scientists, teaching them how develop state of art techniques that address the challenges spanning data integration to knowledge extraction.

Recent invited talks include:

  • MOOCS: Research Collaboration, Data Privacy and the Role of Technology, NSF Meeting on IRB, privacy and big data in Education, Nov 2014.
  • Formulating (big) Data Science Innovations for All, Institute for Big Data Analytics, Dalhousie University, Nov 2014.
  • Data Privacy and Online Education, Panel Discussion on Digital Privacy, MIT Big Data Initiative, Nov 2014.
  • The GigaBeats Project, Joint Statistical Meeting, Boston, MA, August 2014.
  • Knowledge Mining Online Learning Data, Changing How the World Learns Symposium, Taipei, Taiwan, January 2014.
  • Comparative Effectiveness using MIMIC II Clinical Data, Critical Data: Secondary Use of Data from Critical Care, January, 2014.
  • MoocDB: Taming MOOC Big Data while Fostering Collaboration in Online Education Research, MIT XTalks Series, December, 2013.
  • Knowledge Mining Blood Pressure Waveforms: The GigaBEATS Project. Quantitative Medicine Series, October 2013.
  • Scalable Machine Learning to Exploit Big Data for Knowledge Discovery, MIT ILP-EPOCH Taiwan Symposium, July 2013.
  • The GigaBeats Project: Knowledge Discovery Methods for Blood Pressure Waveforms, Big Data in BioMedicine, Stanford Medical School, May 2013.
  • FlexGP: A Scalable System for Factored Learning on the Cloud, Spring CSAIL Industry Affiliates Program Meeting, May 29, 2013.
  • Cloud-Scale Learning with FlexGP, GE Whitney Symposium, Oct 23-24, 2012.

Una-May is an adviser to Aspiring Minds. Co-founded by her former student Varun Aggarwal, Aspiring Minds brings data driven assessment to various aspects of education, training and employment. She advises PatternEx, a Silicon Valley security company preventing data breaches by using AI to extract behavioral patterns from big data. Her most recent research with students has resulted in two patents that have spun out startups: Cardinal Wind, co-founded by Teasha Feldman-Fitzthum and DataSight, co-founded by Will Drevo. A third patent arose from serving as VP Engineering at Icosystem which provides predictive modeling using complexity science.

The author of over 100 academic papers, in 2013 Una-May received the EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe.She is a Young/Jr Fellow of the International Society of Genetic and Evolutionary Computation, now ACM SigEVO. She is the area editor for Data Analytics and Knowledge Discovery for Genetic Programming and Evolvable Machines (Kluwer), and editor for Evolutionary Computation (MIT Press), and action editor for the Journal of Machine Learning Research. She holds a B.Sc. from the University of Calgary, and a M.C.S. and Ph.D. (1995) from Carleton University, Ottawa, Canada.

See the ALFA Group website for more information.

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