@article{a029da953c2a45e69297481e3711413b,
title = "Optimization for Data-Driven Learning and Control",
abstract = "The special issue of Proceedings of the IEEE November 2020 provides a comprehensive overview of modern optimization tools and methods for the purposes of data-driven learning and control. The special issue brings together world-renowned experts from the areas of signal processing, control, optimization, and machine learning, who have contributed a total of 12 articles to this issue. These articles should be accessible to readers with different technical backgrounds, summarize the state-of-the-art theoretical and algorithmic advances in optimization for data-driven learning and control, and they elaborate on the implications of these advances in many real-world applications. Another highlight of these articles is their ability to connect their technical results to real-world applications for the benefit of the diverse readership of this special issue.",
author = "Khan, {Usman A.} and Bajwa, {Waheed U.} and Angelia Nedic and Rabbat, {Michael G.} and Sayed, {Ali H.}",
note = "Funding Information: Dr. Bajwa received the Best in Academics Gold Medal and President{\textquoteright}s Gold Medal in Electrical Engineering from the National University of Sciences and Technology in 2001, the Morgridge Distinguished Graduate Fellowship from the University of Wisconsin– Madison in 2003, the Army Research Office Young Investigator Award in 2014, the National Science Foundation CAREER Award in 2015, the Rutgers University{\textquoteright}s Presidential Merit Award in 2016, the Rutgers University{\textquoteright}s Presidential Fellowship for Teaching Excellence in 2017, and the Rutgers Engineering Governing Council ECE Professor of the Year Award in 2016, 2017, and 2019. He is a co-investigator on a work that received the Cancer Institute of New Jersey{\textquoteright}s Gallo Award for Scientific Excellence in 2017, a coauthor on papers that received best student paper awards at IEEE IVMSP 2016 and IEEE CAMSAP 2017 workshops, and a member of the Class of 2015 National Academy of Engineering Frontiers of Engineering Education Symposium. He served as the Lead Guest Editor for IEEE Signal Processing Magazine—Special Issue on Distributed, Streaming Machine Learning in 2020, the Technical Co-Chair for the IEEE SPAWC 2018 Workshop, the Technical Area Chair of the 2018 Asilomar Conference on Signals, Systems, and Computers, the General Chair for the 2017 DIMACS Workshop on Distributed Optimization, Information Processing, and Learning, and an Associate Editor for IEEE SIGNAL PROCESSING LETTERS from 2014 to 2017. He is also serving as a Senior Area Editor for IEEE SIGNAL PROCESSING LETTERS and an Associate Editor for IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS. Funding Information: He held a postdoctoral position at the GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, USA. In 2011, he joined Tufts University as an Assistant Professor. In Spring 2015, he was a Visiting Professor with KTH, Stockholm, Sweden. He is currently an Associate Professor of electrical and computer engineering (ECE) with Tufts University, Medford, MA, USA, where he is also an Adjunct Professor of computer science. His research interests include signal processing, machine learning, control, and optimization. He has published extensively in these topics with more than 100 papers in journals and conference proceedings and holds multiple patents. Recognition of his work includes the prestigious National Science Foundation (NSF) Career Award, several NSF REU awards, an IEEE journal cover, three best student paper awards in IEEE conferences, and several news articles, including two in IEEE Spectrum.",
year = "2020",
month = nov,
doi = "10.1109/JPROC.2020.3031225",
language = "English (US)",
volume = "108",
pages = "1863--1868",
journal = "Proceedings of the IEEE",
issn = "0018-9219",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "11",
}