The growth of mobile and cloud computing, cyberphysical systems and the internet of things has made scalable (“Big Data”) concurrency important. Actor languages and frameworks have been used some of these large-scale systems, and new implementation and analysis tools are facilitating development of robust actor based software. However, as we scale the complexity of systems, a key limitation of current languages and tools becomes apparent: the difficulty of specifying, programming and reasoning about quantitative, probabilistic and aggregate properties. The talk will describe these limitations and some methods that may be developed to address them.

Speaker Bio

Gul Agha is Professor of Computer Science at the University of Illinois at Urbana-Champaign. Dr. Agha is a Fellow of the IEEE, a recipient of the IEEE Computer Society Meritorious Service Award, and the ACM Recognition of Service Award. He served as Editor-in-Chief of IEEE Parallel and Distributed Technology (1994-98) and of ACM Computing Surveys (1999-2007) and is the currently the EiC of Computing Now (IEEE). His book on Actors, published by MIT Press, is among the most widely cited works. He has published over 200 articles, supervised 29 PhD dissertations, and been cited over 16,000 times. He is a co-founder of Embedor Technologies, providing solutions for infrastructure monitoring using sensor networks