Prof. Alfred Hero Distinguished Professor Lecture

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This lecture is presented by Alfred O. Hero in honor of being named the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science

 “Locating the nodes: from sensor arrays to genomic networks”

 Reception following

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.

MIDAS working group on mobile sensor analytics

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The Michigan Institute for Data Science (MIDAS) is convening a research working group on mobile sensor analytics. Mobile sensors are taking on an increasing presence in our lives. Wearable devices allow for physiological and cognitive monitoring, and behavior modeling for health maintenance, exercise, sports, and entertainment. Sensors in vehicles measure vehicle kinematics, record driver behavior, and increase perimeter awareness. Mobile sensors are becoming essential in areas such as environmental monitoring and epidemiological tracking.

There are significant data science opportunities for theory and application in mobile sensor analytics, including real-time data collection, streaming data analysis, active on-line learning, mobile sensor networks, and energy efficient mobile computing.

Our working group welcomes researchers with interest in mobile sensor analytics in any scientific domain, including but not limited to health, transportation, smart cities, ecology and the environment.

Agenda:

  • Brief presentations about challenges and opportunities in mobile sensor analytics (theory and application);

  • A brief presentation of a list of funding opportunities;

  • Discussion of research ideas and collaboration in the context of grant application and industry partnership.

Please RSVP.  For questions, please contact Jing Liu, Ph.D, MIDAS research specialist (ljing@umich.edu; 734-764-2750).

MIDAS starting research group on mobile sensor analytics

By | Educational, Events, General Interest, Happenings, News

The Michigan Institute for Data Science (MIDAS) is convening a research working group on mobile sensor analytics. Mobile sensors are taking on an increasing presence in our lives. Wearable devices allow for physiological and cognitive monitoring, and behavior modeling for health maintenance, exercise, sports, and entertainment. Sensors in vehicles measure vehicle kinematics, record driver behavior, and increase perimeter awareness. Mobile sensors are becoming essential in areas such as environmental monitoring and epidemiological tracking.

There are significant data science opportunities for theory and application in mobile sensor analytics, including real-time data collection, streaming data analysis, active on-line learning, mobile sensor networks, and energy efficient mobile computing.

Our working group welcomes researchers with interest in mobile sensor analytics in any scientific domain, including but not limited to health, transportation, smart cities, ecology and the environment.

Where and When:

Noon to 2 pm, April 13, 2017

School of Public Health I, Room 7625

Lunch provided

Agenda:

  • Brief presentations about challenges and opportunities in mobile sensor analytics (theory and application);

  • A brief presentation of a list of funding opportunities;

  • Discussion of research ideas and collaboration in the context of grant application and industry partnership.

Future Plans: Based on the interest of participants, MIDAS will alert researchers to relevant funding opportunities, hold follow-up meetings for continued discussion and team formation as ideas crystalize for grant applications, and work with the UM Business Engagement Center to bring in industry partnership.

Please RSVP.  For questions, please contact Jing Liu, Ph.D, MIDAS research specialist (ljing@umich.edu; 734-764-2750).