Profile of Gesualdo Scutari
Thrust Lead - Optimization: Gesualdo Scutari
Associate Professor, School of Industrial Engineering, Purdue University
- University of Rome, La Sapienza, Italy, Electrical Engineering, B.Tech. 2001
- University of Rome, La Sapienza, Italy, Electrical Engineering, M.S. 2003
- University of Rome, La Sapienza, Italy, Electrical Engineering, Ph.D. 2006
Aug. 2021 - Current
Professor, School of Industrial Engineering (IE), Purdue University;
Aug. 2015 - 2021
Associate Professor, School of Industrial Engineering (IE), Purdue University;
Jan. 2011 - Aug. 2015
Assistant Professor, School of Electrical Engineering, SUNY Buffalo, NY;
Jan. 2010 - Dec. 2010
Research Associate, Department of Industrial and Enterprise System Engineering, University of Illinois at Urbana-Champaign, IL;
Sept. 2007 - Dec. 2009
Research Associate, Dept. of Electrical and Computer Engineering, Hong Kong Univ. of Science and Technology (HKUST), Hong Kong;
Sept. 2006 - Aug. 2007
Post-doc, University of Rome, La Sapienza, Italy.
Scutari's research lies in the design, analysis, and distributed/parallel optimization of large-scale (network) systems, with applications in signal processing, networking, medical imaging, game theory, and machine learning. The goal is to develop foundational theories and optimization tools to exploit real world system structures that can lead to computationally efficient and distributed solutions, and apply them to improve systems operations and architectures.
Recent efforts have been devoted to develop new optimization techniques, based on parallel and distributed processing, for efficient analytics on big data of different kind. With pervasive sensors continuously collecting massive amounts of information as well as advances in computing, communication, and storage technologies, this is an era of data deluge. Modeling, processing and ultimately making sense of these massive-scale data sets is expected to bring ground-breaking advances in science and engineering. However, the sheer volume and the increasingly distributed nature of data together with the growing complexity of the data models (nonconvex and nonlinear) present major challenges to modern analytics. Scutari's current research aims at addressing these issues to fully realize the big data blessing.
Scutari is a Felow of IEEE (2021). At Purdue he is the scientific director for the area of Big Data at the Cyber Center, Discovery Park (Oct. 2015-Present). He is the recipient of the 2015 IEEE Signal Processing Society Young Author Best Paper Award, the 2015 AnnaMaria Montelvi Award for Mathematics and Physics (from the Italian Scientists and Scholars of North America Foundation), the 2014 ISSNAF Awards Special Mention, the National Science Foundation 2013 early CAREER award, the 2013 UB Exceptional Scholars Young Investigator Award. His papers have been the winner or the runner-up for the best paper award 4 times at various IEEE conferences, and three journal papers reached the status of highly cited paper (ISI Essential Science Indicators). He has also been an invited (tutorial or plenary) speaker to international conferences (in the area of optimization and signal processing.
Scutari serves (served) on the Editorial Boards of IEEE Transactions on Signal Processing (IEEE Signal Processing Letters); he served on IEEE Signal Processing for Communications and Networking Technical Committee (SPCOM TC) (01/2012-12/2014). He is on Organizing Committee and Technical Program Committee of several IEEE Conferences.