Tarek Abdelzaher

Sohaib and Sara Abbasi Professor

Department of Computer Science
University of Illinois at Urbana Champaign
201 N. Goodwin Ave.
Urbana, IL, 61801
zaher@illinois.edu

Abdelzaher (Ph.D., UMich, 1999) is a Sohaib and Sara Abbasi Professor of CS and Willett Faculty Scholar (UIUC), with over 300 refereed publications in Real-time Computing, Distributed Systems, Sensor Networks, and IoT. He served as Editor-in-Chief of J. Real-Time Systems for 20 years, an AE of IEEE TMC, IEEE TPDS, ACM ToSN, ACM TIoT, and ACM ToIT, among others, and chair of multiple top conferences in his field. Abdelzaher received the IEEE Outstanding Technical Achievement and Leadership Award in Real-time Systems (2012), a Xerox Research Award (2011), and several best paper awards. He is a fellow of IEEE and ACM.


Why do I work on cyber-physical systems?

I am motivated by computing applications that address the needs of individuals, businesses, and society. I am especially interested in the intersection of the logical and physical realms. In this space, computing becomes less obtrusive and a more natural part of the external world. Physical objects acquire the appearance of intelligence due to embedded computation, sensing, learning, and actuation. New applications arise that improve the quality of life (e.g., smart assisted living facilities), enhance social interactions (e.g., social media), improve accessibility of information (e.g., novel sensing and data analytics), and help advance fundamental knowledge in many environmental, biological, and physical disciplines. In this new realm, cyber-physical researchers redefine computer science. New models and paradigms are invented to describe the interaction dynamics between social, information, and physical processes. New underlying theoretical foundations are developed to understand these dynamics. New distributed services are built to seamlessly utilize physical data, social inputs, and machine intelligence and offer new capabilities that advance a myriad of applications. Data mining and machine learning techniques are reimagined for the new application space to better identify data patterns, learn context, and act autonomously without human assistance. I work with (and occasionally lead) multidisciplinary teams that investigate the aforementioned aspects of tomorrow's computing systems.