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DTSTART;TZID=America/New_York:20251218T140000
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DESCRIPTION:Professor Kevin Liang\, Adelphi University\n\n[]\n\nProf. Kevin
  Liang is an assistant professor of physics at Adelphi University. His res
 earch focuses on mathematical optics\, which recently involves the analysi
 s of novel superresolution techniques in which traditional assumptions abo
 ut imaging are challenged. Prior to his position at Adelphi University\, P
 rof. Liang did his post-doctoral work and received his PhD in Optics from 
 The Institute of Optics at the University of Rochester.\n\nAbstract: The f
 undamental task of imaging is to improve one's ability to discern the deta
 ils in a given object scene. This could range from tasks as simple as meas
 uring the distance between two known point-like sources\, or determining t
 he full intensity profile of a complicated\, continuous object distributio
 n. Traditional wisdom in the field dictates that the transverse resolution
  of a linear optical imaging system is limited by the width of the system'
 s diffraction-limited point spread function\; a limitation known as Raylei
 gh's Criterion. Over the past decade\, new quantum-inspired superresolutio
 n techniques\, whose improvement can be measured via well-known statistica
 l metrics such as the Fisher Information\, have been shown to possibly cir
 cumvent Rayleigh's Criterion. The details of these techniques\, and their 
 limitations\, are discussed in this talk.\n\nSpeaker(s): Kevin Liang\n\nVi
 rtual: https://events.vtools.ieee.org/m/517709
LOCATION:Virtual: https://events.vtools.ieee.org/m/517709
ORGANIZER:bentley@adelphi.edu
SEQUENCE:50
SUMMARY:Ideas and Limitations for Improving Imaging Resolution via Quantum-
 Inspired Superresolution
URL;VALUE=URI:https://events.vtools.ieee.org/m/517709
X-ALT-DESC:Description: <br /><p><strong>Professor Kevin Liang\, Adelphi Un
 iversity</strong>&nbsp\;</p>\n<p><img src="https://events.vtools.ieee.org/
 vtools_ui/media/display/2093c1ba-d8da-41d4-ba7e-224d8c9e0cab" alt="" width
 ="300" height="300"></p>\n<p>Prof. Kevin Liang is an assistant professor o
 f physics at Adelphi University. His research focuses on mathematical opti
 cs\, which recently involves the analysis of novel superresolution techniq
 ues in which traditional assumptions about imaging are challenged. Prior t
 o his position at Adelphi University\, Prof. Liang did his post-doctoral w
 ork and received his PhD in Optics from The Institute of Optics at the Uni
 versity of Rochester.&nbsp\;</p>\n<p><strong>Abstract: </strong>The fundam
 ental task of imaging is to improve one's ability to discern the details i
 n a given object scene. This could range from tasks as simple as measuring
  the distance between two known point-like sources\, or determining the fu
 ll intensity profile of a complicated\, continuous object distribution. Tr
 aditional wisdom in the field dictates that the transverse resolution of a
  linear optical imaging system is limited by the width of the system's dif
 fraction-limited point spread function\; a limitation known as Rayleigh's 
 Criterion. Over the past decade\, new quantum-inspired superresolution tec
 hniques\, whose improvement can be measured via well-known statistical met
 rics such as the Fisher Information\, have been shown to possibly circumve
 nt Rayleigh's Criterion. The details of these techniques\, and their limit
 ations\, are discussed in this talk.</p>
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