BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Helsinki BEGIN:DAYLIGHT DTSTART:20260329T040000 TZOFFSETFROM:+0200 TZOFFSETTO:+0300 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:EEST END:DAYLIGHT BEGIN:STANDARD DTSTART:20261025T030000 TZOFFSETFROM:+0300 TZOFFSETTO:+0200 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:EET END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260921T103956Z UID:2A87FF87-191C-4B2C-8ADA-994299EBAAD4 DTSTART;TZID=Europe/Helsinki:20260918T134500 DTEND;TZID=Europe/Helsinki:20260918T143000 DESCRIPTION:Abstract:\n\nConventional cameras capture only a small fraction of the information carried by light. Rich properties such as spectrum\, p olarization\, depth\, coherence\, and fast temporal dynamics are typically discarded\, or require bulky instruments and sequential measurements to r ecover.\n\nIn this talk\, I will describe a different approach to imaging in which photonics\, sensors\, and computational algorithms are designed t ogether to capture much more of the information available from a scene. In verse-designed and unconventional optical elements can encode otherwise in accessible physical information directly into sensor measurements\, while computational methods\, including machine learning\, decode these measurem ents into high-dimensional images. When combined with emerging sensor tech nologies such as event-based cameras\, this approach can also capture dyna mics at timescales far beyond those accessible to conventional frame-based imaging.\n\nI will present examples spanning spectral and polarization im aging\, ultrafast sensing\, computational microscopy\, and compact flat-op tics systems\, with applications ranging from biomedical imaging and indus trial inspection to remote sensing and astronomy. More broadly\, these res ults point toward a transition from cameras designed primarily to form ima ges to information-aware imaging systems that jointly optimize the physics and computation for the information (or task) that ultimately matters. Su ch systems offer new opportunities to dramatically reduce size\, weight\, power\, data volume\, and latency while expanding what cameras can measure .\n\nAgenda: \nBio:\n\nRajesh Menon is a Professor of Electrical and Compu ter Engineering at the Univ. of Utah and Chief Technology Officer of Oblat e Optics\, which is commercializing flat-optics technologies pioneered in his laboratory. His research combines nanofabrication\, computational desi gn\, and optical engineering to develop inverse-designed photonics\, flat lenses\, and unconventional imaging systems. He holds more than 45 patents \, has published extensively in peer-reviewed journals\, and has co-founde d four technology companies to translate research advances into practical technologies. He is a Fellow of Optica and SPIE\, and a Member of the Nati onal Academy of Inventors. His honors include the ICO Prize\, NASA Early-S tage Innovations Award\, NSF CAREER Award\, and IEEE Photonics Society Dis tinguished Lectureship. Rajesh earned his S.M. and Ph.D. from MIT and coll aborates extensively with academic\, industry\, and government partners wo rldwide.\n\nRoom: TB104\, Bldg: Tietotalo\, Korkeakoulunkatu 10\, Tampere\ , Vastra Finlands Lan\, Finland\, FI-33014\, Virtual: https://events.vtool s.ieee.org/m/576438 LOCATION:Room: TB104\, Bldg: Tietotalo\, Korkeakoulunkatu 10\, Tampere\, Va stra Finlands Lan\, Finland\, FI-33014\, Virtual: https://events.vtools.ie ee.org/m/576438 ORGANIZER:ari.visa@tuni.fi SEQUENCE:71 SUMMARY:DL Prof. Rajesh Menon: From Photons to Information: Co-Designed Ima ging Systems for Seeing More URL;VALUE=URI:https://events.vtools.ieee.org/m/576438 X-ALT-DESC:Description: <br /><p class="MsoNormal"><strong><span lang="EN"> Abstract:</span></strong></p>\n<p class="MsoNormal" style="text-align: jus tify\;"><span lang="EN">Conventional cameras capture only a small fraction of the information carried by light. Rich properties such as spectrum\, p olarization\, depth\, coherence\, and fast temporal dynamics are typically discarded\, or require bulky instruments and sequential measurements to r ecover.</span></p>\n<p class="MsoNormal" style="text-align: justify\; text -indent: 36.0pt\;"><span lang="EN">In this talk\, I will describe a differ ent approach to imaging in which photonics\, sensors\, and computational a lgorithms are designed together to capture much more of the information av ailable from a scene. Inverse-designed and unconventional optical elements can encode otherwise inaccessible physical information directly into sens or measurements\, while computational methods\, including machine learning \, decode these measurements into high-dimensional images. When combined w ith emerging sensor technologies such as event-based cameras\, this approa ch can also capture dynamics at timescales far beyond those accessible to conventional frame-based imaging.</span></p>\n<p class="MsoNormal" style=" text-align: justify\; text-indent: 36.0pt\;"><span lang="EN">I will presen t examples spanning spectral and polarization imaging\, ultrafast sensing\ , computational microscopy\, and compact flat-optics systems\, with applic ations ranging from biomedical imaging and industrial inspection to remote sensing and astronomy. More broadly\, these results point toward a transi tion from cameras designed primarily to form images to information-aware i maging systems that jointly optimize the physics and computation for the i nformation (or task) that ultimately matters. Such systems offer new oppor tunities to dramatically reduce size\, weight\, power\, data volume\, and latency while expanding what cameras can measure.</span></p><br /><br />Ag enda: <br /><p class="MsoNormal" style="text-align: justify\;"><strong><sp an lang="EN">Bio:</span></strong></p>\n<p class="MsoNormal" style="text-al ign: justify\;"><span lang="EN">Rajesh Menon is a Professor of Electrical and Computer Engineering at the Univ. of Utah and Chief Technology Officer of Oblate Optics\, which is commercializing flat-optics technologies pion eered in his laboratory. His research combines nanofabrication\, computati onal design\, and optical engineering to develop inverse-designed photonic s\, flat lenses\, and unconventional imaging systems. He holds more than 4 5 patents\, has published extensively in peer-reviewed journals\, and has co-founded four technology companies to translate research advances into p ractical technologies. He is a Fellow of Optica and SPIE\, and a Member of the National Academy of Inventors. His honors include the ICO Prize\, NAS A Early-Stage Innovations Award\, NSF CAREER Award\, and IEEE Photonics So ciety Distinguished Lectureship. Rajesh earned his S.M. and Ph.D. from MIT and collaborates extensively with academic\, industry\, and government pa rtners worldwide.</span></p> END:VEVENT END:VCALENDAR