BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Canada/Eastern BEGIN:DAYLIGHT DTSTART:20210314T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20201101T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20211004T034318Z UID:96691D27-09C3-4D54-8B38-1F679F9B9C9F DTSTART;TZID=Canada/Eastern:20210111T160000 DTEND;TZID=Canada/Eastern:20210111T170000 DESCRIPTION:The U of T Student Chapter of the IEEE Antennas and Propagation Society (AP-S) invites you to the following talk of our 2020-2021 seminar series:\n\n"Inverse Electromagnetics Design with Physics-Driven Neural Ne tworks\," presented by Jonathan A. Fan from Stanford University\, on Monda y\, Jan. 11\, 2021\, 4-5 PM ET.\n\nAbstract: In this talk\, Prof. Fan will present new algorithmic approaches to the inverse design of freeform elec tromagnetic devices. His focus will be on an optimization strategy based o n physics-driven neural networks\, termed GLOnets\, in which the global op timization process is reframed as the training of a generative neural netw ork. Prof. Fan will discuss how this method incorporates physics and physi cal constraints through the interfacing of Maxwell’s equations with mach ine learning\, and he will frame the discussion around examples of metasur faces and thin-film stacks operating near physical design limits. These id eas will help set the stage for hybrid physics- and data-driven approaches to be used in defining the next frontier of electromagnetics engineering. \n\nBio: Jonathan Fan is an Assistant Professor in the Department of Elect rical Engineering at Stanford University\, where he is researching new des ign methodologies and materials approaches to nanophotonic systems. He rec eived his bachelor’s degree with highest honors from Princeton Universit y and his doctorate from Harvard University. He is the recipient of the Ai r Force Young Investigator Award\, Sloan Foundation Fellowship in Physics\ , Packard Foundation Fellowship\, and the Presidential Early Career Award for Scientists and Engineers.\n\nDate: Monday\, Jan.11\, 2021\n\nTime: 4:0 0 PM ET\n\nToronto\, Ontario\, Canada\, Virtual: https://events.vtools.iee e.org/m/255176 LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.o rg/m/255176 ORGANIZER:pz.naseri@gmail.com SEQUENCE:4 SUMMARY:[AP-S Seminar Series] Jonathan A. Fan from Stanford University\, Ja n. 11\, 2021\, 4-5 pm ET URL;VALUE=URI:https://events.vtools.ieee.org/m/255176 X-ALT-DESC:Description: <br /><p>The U of T Student Chapter of the IEEE&nbs p\;Antennas and&nbsp\;Propagation Society (AP-S)&nbsp\;invites you to the following talk of our 2020-2021 seminar series:</p>\n<p>&nbsp\;</p>\n<p><s trong>"Inverse Electromagnetics Design with Physics-Driven Neural Networks \,"</strong><strong>&nbsp\;</strong>presented&nbsp\;by&nbsp\;<strong>Jonat han A. Fan&nbsp\;</strong>from&nbsp\;<strong>Stanford Universit</strong>y\ ,&nbsp\;on<strong>&nbsp\;Monday\,&nbsp\;Jan. 11\, 2021\, 4-5&nbsp\;PM&nbsp \;ET</strong>.&nbsp\;</p>\n<div><strong>&nbsp\;</strong></div>\n<div><stro ng>Abstract:</strong>&nbsp\;In this talk\, Prof. Fan will present new algo rithmic approaches to the inverse design of freeform electromagnetic devic es. His focus will be on an optimization strategy based on physics-driven neural networks\, termed GLOnets\, in which the global optimization proces s is reframed as the training of a generative neural network.&nbsp\; Prof. Fan will discuss how this method incorporates physics and physical constr aints through the interfacing of Maxwell&rsquo\;s equations with machine l earning\, and he will frame the discussion around examples of metasurfaces and thin-film stacks operating near physical design limits. These ideas w ill help set the stage for hybrid physics- and data-driven approaches to b e used in defining the next frontier of electromagnetics engineering.</div >\n<p><strong>Bio:</strong>&nbsp\;&nbsp\;Jonathan Fan is an Assistant Prof essor in the Department of Electrical Engineering at Stanford University\, where he is researching new design methodologies and materials approaches to nanophotonic systems. He received his bachelor&rsquo\;s degree with hi ghest honors from Princeton University and his doctorate from Harvard Univ ersity. He is the recipient of the Air Force Young Investigator Award\, Sl oan Foundation Fellowship in Physics\, Packard Foundation Fellowship\, and the Presidential Early Career Award for Scientists and Engineers.&nbsp\;< /p>\n<p>&nbsp\;</p>\n<p><strong>Date</strong>: Monday\, Jan.<span style="c olor: #000000\;">11</span>\, 2021</p>\n<p><strong>Time</strong>: 4:00 PM E T</p> END:VEVENT END:VCALENDAR