Presented By: Electrical and Computer Engineering
Dist. University Professorship Lecture: Locating the nodes: from sensor arrays to genomic networks
Alfred O. Hero, III
Abstract:
Spatially distributed measurements have been used for hundreds of years to perform geolocation, geodesy and triangulation. In WW1 acoustic sensor arrays were used to locate the direction of cannon fire based on correlation between sensor readings. Sensors in the Internet-of-Things (IoT) auto-locate their nodes based on correlation between received pilot signals. In genomics influential nodes are located in transcriptional or lineage networks based on correlation between omic profiles. Whether the node is a target, a sensor, or a nucleotide sequence, the problem of node localization is of central interest in many disciplines of science and technology. In this talk I will provide perspectives on the general node localization problem, discuss solutions and algorithms, and address future opportunities and challenges.
BIo:
Alfred O. Hero III is the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science and the R. Jamison and Betty Williams Professor of Engineering. He is also the Co-Director of the University's Michigan Institute for Data Science (MIDAS). He is also a professor of Biomedical Engineering and Statistics.
Hero's recent research interests are in high dimensional spatio-temporal data, multi-modal data integration, statistical signal processing, and machine learning. Of particular interest are applications to social networks, network security and forensics, computer vision, and personalized health.
Hero received a B.S. (summa cum laude) from Boston University (1980) and a Ph.D from Princeton University (1984), both in Electrical Engineering. He joined the faculty of the University of Michigan in 1984. He received the University of Michigan Distinguished Faculty Achievement Award (2011), the Stephen S. Attwood Excellence in Engineering Award (2017), the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millenium Medal (2000), and the IEEE Signal Processing Society Technical Achievement Award (2014). In 2015 he received the IEEE Signal Processing Society Award, which is the highest career award bestowed by this Society. Hero was President of the IEEE Signal Processing Society (2006-2008) and was on the Board of Directors of the IEEE (2009-2011) where he served as Director of Division IX (Signals and Applications). He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), and is chair of the Committee on Applied and Theoretical Statistics (CATS) of the US National Academies of Science.
Hero is presenting this talk to commemorate being named the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science.
Spatially distributed measurements have been used for hundreds of years to perform geolocation, geodesy and triangulation. In WW1 acoustic sensor arrays were used to locate the direction of cannon fire based on correlation between sensor readings. Sensors in the Internet-of-Things (IoT) auto-locate their nodes based on correlation between received pilot signals. In genomics influential nodes are located in transcriptional or lineage networks based on correlation between omic profiles. Whether the node is a target, a sensor, or a nucleotide sequence, the problem of node localization is of central interest in many disciplines of science and technology. In this talk I will provide perspectives on the general node localization problem, discuss solutions and algorithms, and address future opportunities and challenges.
BIo:
Alfred O. Hero III is the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science and the R. Jamison and Betty Williams Professor of Engineering. He is also the Co-Director of the University's Michigan Institute for Data Science (MIDAS). He is also a professor of Biomedical Engineering and Statistics.
Hero's recent research interests are in high dimensional spatio-temporal data, multi-modal data integration, statistical signal processing, and machine learning. Of particular interest are applications to social networks, network security and forensics, computer vision, and personalized health.
Hero received a B.S. (summa cum laude) from Boston University (1980) and a Ph.D from Princeton University (1984), both in Electrical Engineering. He joined the faculty of the University of Michigan in 1984. He received the University of Michigan Distinguished Faculty Achievement Award (2011), the Stephen S. Attwood Excellence in Engineering Award (2017), the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millenium Medal (2000), and the IEEE Signal Processing Society Technical Achievement Award (2014). In 2015 he received the IEEE Signal Processing Society Award, which is the highest career award bestowed by this Society. Hero was President of the IEEE Signal Processing Society (2006-2008) and was on the Board of Directors of the IEEE (2009-2011) where he served as Director of Division IX (Signals and Applications). He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), and is chair of the Committee on Applied and Theoretical Statistics (CATS) of the US National Academies of Science.
Hero is presenting this talk to commemorate being named the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science.
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