Draft:David Messinger

American physicist From Wikipedia, the free encyclopedia

David W. Messinger is an American physicist and professor at the Rochester Institute of Technology (RIT), where he holds the Xerox Chair in Imaging Science in the Chester F. Carlson Center for Imaging Science. He served as director of the Center for Imaging Science from 2014 to 2022.[1] His research focuses on hyperspectral imaging and spectral image analysis, with applications ranging from remote sensing for national security to cultural heritage imaging of historical manuscripts and artifacts.[1] He is a Fellow of SPIE and holds a visiting professorship at Durham University.[2]

KnownforSpectral image analysis
Cultural heritage imaging
MISHA imaging system
AwardsFellow, SPIE
Xerox Chair in Imaging Science
Quick facts David W. Messinger, Alma mater ...
David W. Messinger
Alma materClarkson University (B.S.)
Rensselaer Polytechnic Institute (Ph.D.)
Known forSpectral image analysis
Cultural heritage imaging
MISHA imaging system
AwardsFellow, SPIE
Xerox Chair in Imaging Science
Scientific career
FieldsRemote sensing, hyperspectral imaging, imaging science
InstitutionsRochester Institute of Technology
Northrop Grumman
XonTech Inc.
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Education and early career

Messinger received his B.S. in physics from Clarkson University in 1991 and his Ph.D. in physics from Rensselaer Polytechnic Institute in 1998.[3] Before joining academia, he worked as an analyst for XonTech Inc. and on the National Missile Defense program for Northrop Grumman.[1] He was also an Intelligence Community Postdoctoral Research Fellow.[1]

Career at RIT

Messinger joined RIT in 2002.[4] He served as director of the Digital Imaging and Remote Sensing (DIRS) Laboratory from 2007 to 2014, and then as director of the Chester F. Carlson Center for Imaging Science from 2014 to 2022, an academic unit offering bachelor's, master's, and doctoral degrees in imaging science.[1] He has been principal investigator on approximately $8 million in externally sponsored research funding, published over 190 scholarly articles, and advised over 35 master's and doctoral students.[1]

Messinger co-chairs the SPIE conference on Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging.[5]

Imaging science workforce advocacy

In 2013, Messinger and RIT President Bill Destler briefed a congressional panel on the national defense workforce need for imaging scientists and remote sensing specialists, in a hearing sponsored by U.S. Representative Louise Slaughter.[6] The briefing, held at the National Geospatial-Intelligence Agency headquarters, drew upon a 2008 report by the Subcommittee on Technical and Tactical Intelligence for the United States House of Representatives, which called for workforce development in imaging science and partnerships with universities.[6]

Cultural heritage imaging

Messinger's research has expanded from traditional remote sensing into cultural heritage imaging, applying hyperspectral and multispectral imaging techniques to study historical manuscripts, maps, and works of art.[1] He co-directs the Cultural Heritage Imaging Lab at RIT with Juilee Decker and Roger L. Easton Jr.[7]

The team developed the Multispectral Imaging System for Historical Artifacts (MISHA), a low-cost portable imaging system designed to make spectral imaging accessible to libraries, archives, and museums. The project was funded by a grant from the National Endowment for the Humanities.[7] The system enables scholars to recover obscured and illegible text on historical documents using imaging outside the sensitivity range of the human visual system.[8]

Messinger holds a visiting professorship at the Institute of Medieval and Early Modern Studies at Durham University, where he spent a sabbatical in 2023–24 working with "Team Pigment" to study materials, methods, and content of historical artifacts using spectral imaging techniques.[2]

His cultural heritage publications include work on automatic pigment classification in illuminated manuscripts using hyperspectral reflectance data,[9] virtual cleaning of works of art using deep generative networks,[10] and palimpsest text separation.[11]

Honors and awards

References

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