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Inference, Information and Decision Systems Group

The Inference, Information and Decision (I.I.D.) Systems Group is led by Amin Karbasi. The research in I.I.D. is at the intersection of learning theory, large-scale networks, and optimum information processing. We devise new algorithms, build models, analyze the behavior of large and complex networks, and develop systems that can automatically acquire and reason about highly uncertain information. Our application domains include interactive recommender systems, social and neural networks, and optimal experimental design.

May 17, 2016

Tassiulas receives 2016 IEEE Koji Kobayashi Computers and Communications Award

Professor Leandros Tassiulas has received the 2016 IEEE Koji Kobayashi Computers and Communications Award For contributions to the scheduling and stability analysis of networks. 

Leandros Tassiulas has revolutionized how scheduling and stability analysis are performed in communications networks, providing dynamic resource allocation tools to improve performance of wireless networks and Internet switches. Developing control algorithms based on a sound mathematical foundation as an alternative to heuristic approaches, Tassiulas introduced the Max-Weight scheduling algorithm for achieving maximum throughput in systems with conflicting resources as well as the Backpressure routing algorithm for end-to-end traffic forwarding. His Maximum Connected Queue algorithm introduced the concept of opportunistic scheduling that became part of most wireless standards since 3G. Together, these three algorithms provide the basis for cross-layer network design in today’s wireless networks. 

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