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Dr. Guang Gao, a distinguished professor of electrical and computer engineering, along with Professor Roberto Giorgi, an associate professor at the Università degli Studi di Siena in Siena, Italy and primary investigator (Coordinator / Scientific Manager) of the TeraFlux project. Pictured here with Ken Barner, chair of the Department of Electrical and Computer Engineering. The TeraFlux project seeks to exploit dataflow parallelism in teradevice computing and propose a complete solution to harness large-scale parallelism in an efficient way. The University of Delaware recently joined the TeraFlux project and received a grant connected to the project from the EU.
Ishtiaque Navid, PhD student in electrical and computer engineering, on the North Campus of the University of Michigan in Ann Arbor, on Friday, October 14, 2022.
Photo: Brenda Ahearn/University of Michigan, College of Engineering, Communications and Marketing
Dr. Guang Gao, a distinguished professor of electrical and computer engineering, along with Professor Roberto Giorgi, an associate professor at the Università degli Studi di Siena in Siena, Italy and primary investigator (Coordinator / Scientific Manager) of the TeraFlux project. Pictured here with Ken Barner, chair of the Department of Electrical and Computer Engineering, and grad students. The TeraFlux project seeks to exploit dataflow parallelism in teradevice computing and propose a complete solution to harness large-scale parallelism in an efficient way. The University of Delaware recently joined the TeraFlux project and received a grant connected to the project from the EU.
Georgios Giannakis, PhD
Professor of Electrical and Computer Engineering at the University of Minnesota
Director of the Digital Technology Center
Monday, Nov. 18, 2019, 3:30 p.m.
Donna E. Shalala Student Center, Senate Room 302
1300 Miller Drive Coral Gables, FL 33146
Abstract
We live in an era of data deluge. Pervasive sensors collect massive amounts of information on every bit of our lives, churning out enormous streams of raw data in various formats. Mining information and learning from unprecedented volumes of data promises to limit the spread of epidemics and diseases, identify trends in financial markets, learn the dynamics of emergent social-computational systems, and also protect critical infrastructure including the smart grid and the Internet’s backbone network. While Big Data can be definitely perceived as a big blessing, big challenges also arise with large-scale datasets. This talk will overview challenges and opportunities emerging in the analytical and algorithmic foundations that are widely referred to as Data Science, and Network Science, the latter for data residing on graphs formed by agents that are interconnected (or networked) either physically or through their interdependencies.
Georgios Giannakis, PhD, received his diploma in Electrical Engineering from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. He was with the U. of Virginia from 1987 to 1998, and since 1999 he has been a professor with the U. of Minnesota, where he holds a Chair in Wireless Communications, a University of Minnesota McKnight Presidential Chair in ECE, and serves as director of the Digital Technology Center. His general interests span the areas of communications, networking and statistical signal processing – subjects on which he has published more than 450 journal papers, 750 conference papers, 25 book chapters, two edited books and two research monographs (h-index 143). Current research focuses on data science and network science with applications to social, brain, and power networks with renewables. He is the (co-) inventor of 33 patents issued, and the (co-) recipient of 9 best journal paper awards from the IEEE Signal Processing (SP) and Communications Societies. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), and the inaugural IEEE Fourier Tech. Field Award (2015). He is a Fellow of EURASIP, and has served the IEEE in various posts including that of a Distinguished Lecturer.
Georgios Giannakis, PhD
Professor of Electrical and Computer Engineering at the University of Minnesota
Director of the Digital Technology Center
Monday, Nov. 18, 2019, 3:30 p.m.
Donna E. Shalala Student Center, Senate Room 302
1300 Miller Drive Coral Gables, FL 33146
Abstract
We live in an era of data deluge. Pervasive sensors collect massive amounts of information on every bit of our lives, churning out enormous streams of raw data in various formats. Mining information and learning from unprecedented volumes of data promises to limit the spread of epidemics and diseases, identify trends in financial markets, learn the dynamics of emergent social-computational systems, and also protect critical infrastructure including the smart grid and the Internet’s backbone network. While Big Data can be definitely perceived as a big blessing, big challenges also arise with large-scale datasets. This talk will overview challenges and opportunities emerging in the analytical and algorithmic foundations that are widely referred to as Data Science, and Network Science, the latter for data residing on graphs formed by agents that are interconnected (or networked) either physically or through their interdependencies.
Georgios Giannakis, PhD, received his diploma in Electrical Engineering from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. He was with the U. of Virginia from 1987 to 1998, and since 1999 he has been a professor with the U. of Minnesota, where he holds a Chair in Wireless Communications, a University of Minnesota McKnight Presidential Chair in ECE, and serves as director of the Digital Technology Center. His general interests span the areas of communications, networking and statistical signal processing – subjects on which he has published more than 450 journal papers, 750 conference papers, 25 book chapters, two edited books and two research monographs (h-index 143). Current research focuses on data science and network science with applications to social, brain, and power networks with renewables. He is the (co-) inventor of 33 patents issued, and the (co-) recipient of 9 best journal paper awards from the IEEE Signal Processing (SP) and Communications Societies. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), and the inaugural IEEE Fourier Tech. Field Award (2015). He is a Fellow of EURASIP, and has served the IEEE in various posts including that of a Distinguished Lecturer.
Georgios Giannakis, PhD
Professor of Electrical and Computer Engineering at the University of Minnesota
Director of the Digital Technology Center
Monday, Nov. 18, 2019, 3:30 p.m.
Donna E. Shalala Student Center, Senate Room 302
1300 Miller Drive Coral Gables, FL 33146
Abstract
We live in an era of data deluge. Pervasive sensors collect massive amounts of information on every bit of our lives, churning out enormous streams of raw data in various formats. Mining information and learning from unprecedented volumes of data promises to limit the spread of epidemics and diseases, identify trends in financial markets, learn the dynamics of emergent social-computational systems, and also protect critical infrastructure including the smart grid and the Internet’s backbone network. While Big Data can be definitely perceived as a big blessing, big challenges also arise with large-scale datasets. This talk will overview challenges and opportunities emerging in the analytical and algorithmic foundations that are widely referred to as Data Science, and Network Science, the latter for data residing on graphs formed by agents that are interconnected (or networked) either physically or through their interdependencies.
Georgios Giannakis, PhD, received his diploma in Electrical Engineering from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. He was with the U. of Virginia from 1987 to 1998, and since 1999 he has been a professor with the U. of Minnesota, where he holds a Chair in Wireless Communications, a University of Minnesota McKnight Presidential Chair in ECE, and serves as director of the Digital Technology Center. His general interests span the areas of communications, networking and statistical signal processing – subjects on which he has published more than 450 journal papers, 750 conference papers, 25 book chapters, two edited books and two research monographs (h-index 143). Current research focuses on data science and network science with applications to social, brain, and power networks with renewables. He is the (co-) inventor of 33 patents issued, and the (co-) recipient of 9 best journal paper awards from the IEEE Signal Processing (SP) and Communications Societies. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), and the inaugural IEEE Fourier Tech. Field Award (2015). He is a Fellow of EURASIP, and has served the IEEE in various posts including that of a Distinguished Lecturer.
Purdue University’s Elmore Family School of Electrical and Computer Engineering today (Sept. 29) celebrated the completion of new, cutting-edge research space. The Chiminski Family Collaborative Research Hub is located on the second floor of the Materials and Electrical Engineering Building (MSEE). It was made possible by a generous gift from alumnus John R. Chiminski and his wife Laura A. Chiminski.
Purdue University’s Elmore Family School of Electrical and Computer Engineering today (Sept. 29) celebrated the completion of new, cutting-edge research space. The Chiminski Family Collaborative Research Hub is located on the second floor of the Materials and Electrical Engineering Building (MSEE). It was made possible by a generous gift from alumnus John R. Chiminski and his wife Laura A. Chiminski.
Georgios Giannakis, PhD
Professor of Electrical and Computer Engineering at the University of Minnesota
Director of the Digital Technology Center
Monday, Nov. 18, 2019, 3:30 p.m.
Donna E. Shalala Student Center, Senate Room 302
1300 Miller Drive Coral Gables, FL 33146
Abstract
We live in an era of data deluge. Pervasive sensors collect massive amounts of information on every bit of our lives, churning out enormous streams of raw data in various formats. Mining information and learning from unprecedented volumes of data promises to limit the spread of epidemics and diseases, identify trends in financial markets, learn the dynamics of emergent social-computational systems, and also protect critical infrastructure including the smart grid and the Internet’s backbone network. While Big Data can be definitely perceived as a big blessing, big challenges also arise with large-scale datasets. This talk will overview challenges and opportunities emerging in the analytical and algorithmic foundations that are widely referred to as Data Science, and Network Science, the latter for data residing on graphs formed by agents that are interconnected (or networked) either physically or through their interdependencies.
Georgios Giannakis, PhD, received his diploma in Electrical Engineering from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. He was with the U. of Virginia from 1987 to 1998, and since 1999 he has been a professor with the U. of Minnesota, where he holds a Chair in Wireless Communications, a University of Minnesota McKnight Presidential Chair in ECE, and serves as director of the Digital Technology Center. His general interests span the areas of communications, networking and statistical signal processing – subjects on which he has published more than 450 journal papers, 750 conference papers, 25 book chapters, two edited books and two research monographs (h-index 143). Current research focuses on data science and network science with applications to social, brain, and power networks with renewables. He is the (co-) inventor of 33 patents issued, and the (co-) recipient of 9 best journal paper awards from the IEEE Signal Processing (SP) and Communications Societies. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), and the inaugural IEEE Fourier Tech. Field Award (2015). He is a Fellow of EURASIP, and has served the IEEE in various posts including that of a Distinguished Lecturer.
Jessica Yoshimi and Benjamin Gelsey receive the Computer Engineering/Computer Science Outstanding Student Awards.
Georgios Giannakis, PhD
Professor of Electrical and Computer Engineering at the University of Minnesota
Director of the Digital Technology Center
Monday, Nov. 18, 2019, 3:30 p.m.
Donna E. Shalala Student Center, Senate Room 302
1300 Miller Drive Coral Gables, FL 33146
Abstract
We live in an era of data deluge. Pervasive sensors collect massive amounts of information on every bit of our lives, churning out enormous streams of raw data in various formats. Mining information and learning from unprecedented volumes of data promises to limit the spread of epidemics and diseases, identify trends in financial markets, learn the dynamics of emergent social-computational systems, and also protect critical infrastructure including the smart grid and the Internet’s backbone network. While Big Data can be definitely perceived as a big blessing, big challenges also arise with large-scale datasets. This talk will overview challenges and opportunities emerging in the analytical and algorithmic foundations that are widely referred to as Data Science, and Network Science, the latter for data residing on graphs formed by agents that are interconnected (or networked) either physically or through their interdependencies.
Georgios Giannakis, PhD, received his diploma in Electrical Engineering from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. He was with the U. of Virginia from 1987 to 1998, and since 1999 he has been a professor with the U. of Minnesota, where he holds a Chair in Wireless Communications, a University of Minnesota McKnight Presidential Chair in ECE, and serves as director of the Digital Technology Center. His general interests span the areas of communications, networking and statistical signal processing – subjects on which he has published more than 450 journal papers, 750 conference papers, 25 book chapters, two edited books and two research monographs (h-index 143). Current research focuses on data science and network science with applications to social, brain, and power networks with renewables. He is the (co-) inventor of 33 patents issued, and the (co-) recipient of 9 best journal paper awards from the IEEE Signal Processing (SP) and Communications Societies. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), and the inaugural IEEE Fourier Tech. Field Award (2015). He is a Fellow of EURASIP, and has served the IEEE in various posts including that of a Distinguished Lecturer.
On Sept. 9, 2022, the Elmore Family School of Electrical and Computer Engineering celebrated the naming of the Max W and Maileen Brown Family Hall of Electrical Engineering. We thank alumnus Max W Brown , his wife Maileen, and their children Max G and Ash for their support of our School!
2023 Winter Party
School of Electrical & Computer Engineering
College of Engineering
Georgia Institute of Technology
Georgios Giannakis, PhD
Professor of Electrical and Computer Engineering at the University of Minnesota
Director of the Digital Technology Center
Monday, Nov. 18, 2019, 3:30 p.m.
Donna E. Shalala Student Center, Senate Room 302
1300 Miller Drive Coral Gables, FL 33146
Abstract
We live in an era of data deluge. Pervasive sensors collect massive amounts of information on every bit of our lives, churning out enormous streams of raw data in various formats. Mining information and learning from unprecedented volumes of data promises to limit the spread of epidemics and diseases, identify trends in financial markets, learn the dynamics of emergent social-computational systems, and also protect critical infrastructure including the smart grid and the Internet’s backbone network. While Big Data can be definitely perceived as a big blessing, big challenges also arise with large-scale datasets. This talk will overview challenges and opportunities emerging in the analytical and algorithmic foundations that are widely referred to as Data Science, and Network Science, the latter for data residing on graphs formed by agents that are interconnected (or networked) either physically or through their interdependencies.
Georgios Giannakis, PhD, received his diploma in Electrical Engineering from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. He was with the U. of Virginia from 1987 to 1998, and since 1999 he has been a professor with the U. of Minnesota, where he holds a Chair in Wireless Communications, a University of Minnesota McKnight Presidential Chair in ECE, and serves as director of the Digital Technology Center. His general interests span the areas of communications, networking and statistical signal processing – subjects on which he has published more than 450 journal papers, 750 conference papers, 25 book chapters, two edited books and two research monographs (h-index 143). Current research focuses on data science and network science with applications to social, brain, and power networks with renewables. He is the (co-) inventor of 33 patents issued, and the (co-) recipient of 9 best journal paper awards from the IEEE Signal Processing (SP) and Communications Societies. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), and the inaugural IEEE Fourier Tech. Field Award (2015). He is a Fellow of EURASIP, and has served the IEEE in various posts including that of a Distinguished Lecturer.
2014 Roger Webb Awards Program
Electrical & Computer Engineering
College of Engineering
Georgia Institute of Technology