TITLE: Emergent Phenomena in Algorithms and Applications 

ABSTRACT:

How do you control a set of asynchronous agents with limited computational ability and get them to perform a useful collective task?  This and related questions lie at the heart of programmable active matter and swarm robotics.  We will see how lessons learned from algorithms and physical systems, such as phase transitions, can be leveraged to force interesting collective behaviors.  We will also explore how phase transitions greatly affect the efficiency of simple Markov chains used for sampling and yield insights for problems from other fields, such as particle systems, colloids, and models of segregation.

BIO:

Dana Randall is the co-executive director of the Institute for Data Engineering and Science, the ADVANCE Professor of Computing, and an adjunct professor of mathematics at the Georgia Institute of Technology. Randall received her A.B. in mathematics from Harvard and her Ph.D. in computer science from the University of California at Berkeley. Her research in randomized algorithms and stochastic processes bridges computer science, discrete mathematics, and statistical physics.     

She is a fellow of the American Mathematical Society (AMS) and a national associate of the National Academies, as well as a former Sloan fellow and NSF CAREER award recipient. Randall has been the program chair for the SIAM Symposium on Discrete Algorithms in 2011 and the SIAM Conference on Discrete Mathematics in 2016, and was previously director of the Algorithms and Randomness Center at Georgia Tech.