BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20250309T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20251102T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260124T050353Z UID:D9C711AE-266F-4C69-9B8F-AC891B5D6124 DTSTART;TZID=America/New_York:20250807T180000 DTEND;TZID=America/New_York:20250807T190000 DESCRIPTION:Special Presentation by Dr. Joongheon Kim (Korea U.\, Korea)\n\ nCo-Hosted by the Future Networks AI/ML and Quantum IT working groups\n\nD ate/Time: Thursday\, 7 August 2025 @ 6 PM EDT\n\nPDH Certificate: while ba sic attendance is free\, this course also offers one (1) Professional Deve lopment Hour (PDH) for a nominal fee\; please choose the appropriate "Regi stration Fee" when registering\; additional terms and conditions apply.\n\ nTopic:\n\nQuantum Reinforcement Learning: Algorithms and Applications\n\n Abstract:\n\nQuantum Reinforcement Learning (QRL) sits at the frontier whe re quantum computing and adaptive decision-making converge\, offering the potential to fundamentally reshape sequential decision-making in complex e nvironments. This tutorial provides a structured and accessible introducti on to QRL\, covering theoretical foundations\, algorithmic frameworks\, an d emerging real-world applications. Participants will learn key concepts s uch as variational quantum policies\, quantum-enhanced exploration\, QRL w ith recurrent policies and distributed/multi-agent quantum reinforcement l earning. The tutorial also presents practical use cases of QRL in communic ation networks\, financial modeling\, and autonomous systems. Through both conceptual lectures and hands-on demonstrations\, attendees will gain act ionable insights into building quantum-enhanced learning systems.\n\nSpeak er:\n\n[]\nJoongheon Kim has been with Korea University\, Seoul\, Korea\, since 2019\, where he is currently an associate professor at the School of Electrical Engineering. He received B.S. and M.S. degrees in computer sci ence and engineering from Korea University\, Seoul\, Korea\, in 2004 and 2 006\; and the Ph.D. degree in computer science from the University of Sout hern California (USC)\, Los Angeles\, CA\, USA\, in 2014. Before joining K orea University\, he was a research engineer with LG Electronics\, Seoul\, Korea\, from 2006 to 2009\; a systems engineer with Intel Corporation\, S anta Clara\, CA\, USA\, from 2013 to 2016\; an assistant professor with Ch ung-Ang University\, Seoul\, Korea\, from 2016 to 2019. He also visited Se oul National University Hospital\, Seoul\, Korea. He serves as editor for IEEE Communications Surveys and Tutorials\, IEEE Transactions on Vehicular Technology\, and IEEE Internet of Things Journal. He was a recipient of A nnenberg Graduate Fellowship with his Ph.D. admission from USC (2009)\, In tel Corporation Next Generation and Standards (NGS) Division Recognition A ward (2015)\, IEEE Systems Journal Best Paper Award (2020)\, IEEE ComSoc M ultimedia Communications Technical Committee (MMTC) Outstanding Young Rese archer Award (2020)\, and IEEE ComSoc MMTC Best Journal Paper Award (2021) .\n\nCo-sponsored by: Future Networks Artificial Intelligence & Machine Le arning (AIML) Working Group\n\nVirtual: https://events.vtools.ieee.org/m/4 91420 LOCATION:Virtual: https://events.vtools.ieee.org/m/491420 ORGANIZER:baw@ieee.org SEQUENCE:73 SUMMARY:Quantum Reinforcement Learning (QRL): Algorithms and Applications URL;VALUE=URI:https://events.vtools.ieee.org/m/491420 X-ALT-DESC:Description: <br /><p class="MsoNormal" style="margin-top: .25in \;"><img src="https://events.vtools.ieee.org/vtools_ui/media/display/da20c 1b8-b3d9-4ba9-a7cd-1b1bbebbfeb6" width="750" height="197"></p>\n<p class=" MsoNormal" style="margin-top: 12.0pt\;">Special Presentation by<strong> Dr . Joongheon Kim (Korea U.\, Korea)</strong></p>\n<p class="MsoNormal" styl e="margin-top: 12.0pt\;">Co-Hosted by the Future Networks<strong> AI/ML </ strong>and<strong> Quantum IT working groups</strong></p>\n<p class="MsoNo rmal" style="margin-top: 12.0pt\;"><strong><span style="font-size: 14.0pt\ ; font-family: Copperplate\; mso-fareast-font-family: PMingLiU\; mso-farea st-theme-font: minor-fareast\; mso-bidi-font-family: Arial\; mso-bidi-them e-font: minor-bidi\; mso-ansi-language: EN-US\; mso-fareast-language: ZH-T W\; mso-bidi-language: AR-SA\;">Date/Time</span></strong><span style="font -size: 12.0pt\; font-family: 'Calibri'\,sans-serif\; mso-ascii-theme-font: minor-latin\; mso-fareast-font-family: PMingLiU\; mso-fareast-theme-font: minor-fareast\; mso-hansi-theme-font: minor-latin\; mso-bidi-font-family: Arial\; mso-bidi-theme-font: minor-bidi\; mso-ansi-language: EN-US\; mso- fareast-language: ZH-TW\; mso-bidi-language: AR-SA\;">: <strong>Thursday\, 7 August 2025</strong><strong> @ 6 PM EDT</strong></span></p>\n<p class=" MsoNormal" style="margin-top: 12.0pt\;"><span style="font-size: 12.0pt\; f ont-family: 'Calibri'\,sans-serif\; mso-ascii-theme-font: minor-latin\; ms o-fareast-font-family: PMingLiU\; mso-fareast-theme-font: minor-fareast\; mso-hansi-theme-font: minor-latin\; mso-bidi-font-family: Arial\; mso-bidi -theme-font: minor-bidi\; mso-ansi-language: EN-US\; mso-fareast-language: ZH-TW\; mso-bidi-language: AR-SA\;"><em><strong><span style="font-size: 1 4.0pt\; font-family: Copperplate\; mso-fareast-font-family: PMingLiU\; mso -fareast-theme-font: minor-fareast\; mso-bidi-font-family: Arial\; mso-bid i-theme-font: minor-bidi\; mso-ansi-language: EN-US\; mso-fareast-language : ZH-TW\; mso-bidi-language: AR-SA\;">PDH Certificate</span>:</strong> whi le basic attendance is free\, this course also offers one (1) Professional Development Hour (PDH) for a nominal fee\; please choose the appropriate "Registration Fee" when registering\; additional terms and conditions appl y.</em></span></p>\n<p class="MsoNormal" style="margin-top: .25in\;"><stro ng><u><span style="font-size: 16.0pt\; font-family: Copperplate\;">Topic</ span></u></strong><strong><span style="font-size: 16.0pt\; font-family: Co pperplate\;">:</span></strong></p>\n<p class="MsoNormal"><span style="font -size: 21.333334px\;"><strong>Quantum Reinforcement Learning: Algorithms a nd Applications</strong></span></p>\n<p class="MsoNormal" style="margin-to p: .25in\;"><strong><u><span style="font-size: 16.0pt\; font-family: Coppe rplate\;">Abstract</span></u></strong><strong><span style="font-size: 16.0 pt\; font-family: Copperplate\;">:</span></strong></p>\n<p class="MsoNorma l">Quantum Reinforcement Learning (QRL) sits at the frontier where quantum computing and adaptive decision-making converge\, offering the potential to fundamentally reshape sequential decision-making in complex environment s. This tutorial provides a structured and accessible introduction to QRL\ , covering theoretical foundations\, algorithmic frameworks\, and emerging real-world applications. Participants will learn key concepts such as var iational quantum policies\, quantum-enhanced exploration\, QRL with recurr ent policies and distributed/multi-agent quantum reinforcement learning. T he tutorial also presents practical use cases of QRL in communication netw orks\, financial modeling\, and autonomous systems. Through both conceptua l lectures and hands-on demonstrations\, attendees will gain actionable in sights into building quantum-enhanced learning systems.</p>\n<p><strong><s pan style="font-size: 16.0pt\; font-family: Copperplate\;"><u>Speaker</u>: </span></strong></p>\n<table style="border-collapse: collapse\; width: 100 %\;" border="1"><colgroup><col style="width: 16.122841%\;"><col style="wid th: 83.78119%\;"></colgroup>\n<tbody>\n<tr>\n<td><img src="https://events. vtools.ieee.org/vtools_ui/media/display/b728f410-14db-4d8d-b1ed-67f6a9aead 7a" alt="" width="150" height="180"></td>\n<td>\n<p class="MsoNormal" styl e="margin-top: 6.0pt\;"><strong>Joongheon Kim</strong> has been with Korea University\, Seoul\, Korea\, since 2019\, where he is currently an associ ate professor at the School of Electrical Engineering. He received B.S. an d M.S. degrees in computer science and engineering from Korea University\, Seoul\, Korea\, in 2004 and 2006\; and the Ph.D. degree in computer scien ce from the University of Southern California (USC)\, Los Angeles\, CA\, U SA\, in 2014. Before joining Korea University\, he was a research engineer with LG Electronics\, Seoul\, Korea\, from 2006 to 2009\; a systems engin eer with Intel Corporation\, Santa Clara\, CA\, USA\, from 2013 to 2016\; an assistant professor with Chung-Ang University\, Seoul\, Korea\, from 20 16 to 2019. He also visited Seoul National University Hospital\, Seoul\, K orea. He serves as editor for IEEE Communications Surveys and Tutorials\, IEEE Transactions on Vehicular Technology\, and IEEE Internet of Things Jo urnal. He was a recipient of Annenberg Graduate Fellowship with his Ph.D. admission from USC (2009)\, Intel Corporation Next Generation and Standard s (NGS) Division Recognition Award (2015)\, IEEE Systems Journal Best Pape r Award (2020)\, IEEE ComSoc Multimedia Communications Technical Committee (MMTC) Outstanding Young Researcher Award (2020)\, and IEEE ComSoc MMTC B est Journal Paper Award (2021).</p>\n<p class="MsoNormal" style="margin-to p: 6.0pt\;">&nbsp\;</p>\n</td>\n</tr>\n</tbody>\n</table> END:VEVENT END:VCALENDAR