For Kids

Evolution in Action!



Taught by Una-May O’Reilly, PhD and Erik Hemberg, PhD; Evolution in Action! is an active learning workshop introducing computational thinking for kids 10-14. The exercises teach the fundamentals of computational thinking by having the kids or act out algorithms in the classroom. This workshop encourages kids to think logically and computationally, teaching how to problem-solve without using a computer!

The Evolution in Action! workshop offers kids a fun way to explore concepts related to computational thinking by participating in open-ended, group exercises that integrate concepts from game theory and evolution. Evolution in Action! exercises administer simple but profound ways for kids to think about the procedural aspects of processes and systems they see in the world. We believe there's a lot of computation going on in the world and our goal is to develop with each child an implicit awareness of this in subtle, kid-friendly ways.

The Evolution in Action! workshop exercises are a great example of how computer science and computational thinking can be introduced and integrated with different facets of learning. To promote success in the modern world, we must foster innovation, invention, and problem solving. To do this our kids need to learn to think in a computational way, acquiring the ability to tackle open ended problems which are so common in the world.

All children must be accompanied by an adult. All children must be registered for this workshop to attend. Email us at evoinact at mit.edu to register. Registration deadline for Evolution in Action! is July 10.


Una-May O'Reilly

Una-May O'Reilly 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.

Her research is in the design of scalable Artificial Intelligence systems that execute on a range of hardware systems: GPUs, workstations, grids, clusters, clouds and volunteer compute networks. These systems include machine learning components such as evolutionary algorithms (e.g. genetic programming, genetic algorithms and learning classifiers), classification, non-linear regression, and forecasting algorithms. They span the interpretation and analysis of raw data, through inference on conditioned exemplar data, to the deployment and evaluation of learned “algorithmic machines” in the original application context.

Una-May received the EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe in 2013. She is a Junior Fellow (elected before age 40) of the International Society of Genetic and Evolutionary Computation, now ACM Sig-EVO. She now serves as Vice-Chair of ACM SigEVO. She 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. IIn 2013, with Anna Esparcia, Anniko Ekart and Gabriela Ochoa she inaugurated the Women@GECCO meeting and chairs the group. 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.

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

Erik Hemberg

Erik Hemberg is a Post Doctoral Associate with the ALFA group at CSAIL at MIT. He received his Ph.D in Computer Science from University College Dublin, Ireland in 2010 and has a M.Sc from Chalmers University of Technology, Sweden.

In 2013, Hemberg and O'Reilly co-taught a 1 week, full time course on EC at Shantou University in China employing interactive learning activities and other means of engaging learners to gain a clear, tangible, experience-based abstract understanding of evolution at a level above and beyond textbook biology. They are developing and delivering a extension which is a small private online course (SPOC) course on Evolutionary Processes and Computation for Shantou University, China. email:hembergerik at csail dot mit dot edu

Nicole Hoffman

Nicole Hoffman is Project Assistant for ALFA group, CSAIL, MIT. Nicole graduated from Emmanuel College in Boston, MA with a BA in Sociology and American History. Nicole came on board at ALFA in the spring of 2015 to provide her organizational expertise to the group. She assists with organizational and coordination aspects of student, industry, and government contracted projects. Nicole has been vital in the coordination of the Evolution in Action! workshop at GECCO 2016, Denver. She was assistant teacher at Evolution in Action! at Charlestown High in Dec 2015.