BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Denver BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0700 TZOFFSETTO:-0600 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:MDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20251102T010000 TZOFFSETFROM:-0600 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:MST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20251229T002433Z UID:AF5B4A03-9088-4C79-8C63-C809977F03D3 DTSTART;TZID=America/Denver:20251119T180000 DTEND;TZID=America/Denver:20251119T200000 DESCRIPTION:Dr. Yuhong Liu\, Ph.D.\n\nAssociate Professor – Santa Clara U niversity\nIEEE Computer Society Board of Governors Member | Chair – Geo graphic Activities Committee\n\nDr. Yuhong Liu is an Associate Professor i n the Department of Computer Science and Engineering at Santa Clara Univer sity. She received her B.S. and M.S. degrees from Beijing University of Po sts and Telecommunications in 2004 and 2007\, and her Ph.D. degree from th e University of Rhode Island in 2012.\n\nHer research focuses on responsib le and trustworthy AI\, security and privacy in Agentic AI\, edge intellig ence\, IoT\, and Blockchain. She has authored over 100 peer-reviewed paper s and serves as an Associate Editor for IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)\, IEEE Transactions on Service Comput ing (TSC)\, Multimedia Tools and Applications (MTAP)\, and APSIPA Transact ions on Signal and Information Processing (TSIP).\n\nShe also serves as a member of the IEEE Computer Society Board of Governors\, Chair of the Geog raphic Activities Committee\, Treasurer of the T&C Board\, an IEEE Disting uished Visitor (2022–2024)\, and an APSIPA Distinguished Lecturer (2021 –2022).\n\nPresentation: Agentic AI – Powering the Next Wave of Energy Autonomy\n\nAbstract:\n\nThe energy sector is undergoing rapid transforma tion\, driven by the rise of renewables\, decentralization\, and electrifi cation. Utilities\, operators\, and enterprises face increasing pressure t o manage complexity\, volatility\, and ambitious sustainability goals. Age ntic AI for energy autonomy offers a powerful paradigm by enabling autonom ous\, goal-driven agents that optimize generation\, distribution\, and con sumption in real time.\n\nUnlike traditional automation\, agentic systems are adaptive\, self-directed\, and capable of long-horizon decision-making . They can coordinate distributed resources\, ensure grid stability\, and manage storage and demand response with minimal oversight. This talk explo res the emerging research landscape\, highlights opportunities\, and showc ases case studies that illustrate the potential and challenges of Agentic AI in energy systems.\n\nSpeaker(s): Dr. Yuhong Liu\, \n\nVirtual: https:/ /events.vtools.ieee.org/m/510472 LOCATION:Virtual: https://events.vtools.ieee.org/m/510472 ORGANIZER:gowansj@ieee.org SEQUENCE:19 SUMMARY:CIR: Agentic AI – Powering the Next Wave of Energy Autonomy URL;VALUE=URI:https://events.vtools.ieee.org/m/510472 X-ALT-DESC:Description: <br /><h3><span style="font-size: 12.0pt\; line-hei ght: 115%\; color: windowtext\;">Dr. Yuhong Liu\, Ph.D.<span style="mso-sp acerun: yes\;">&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nb sp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\; &nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbs p\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;& nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp \;&nbsp\; </span></span></h3>\n<p class="MsoNormal">Associate Professor &n dash\; Santa Clara University<br>IEEE Computer Society Board of Governors Member | Chair &ndash\; Geographic Activities Committee</p>\n<h4>&nbsp\;</ h4>\n<p class="MsoNormal" style="text-align: justify\; text-justify: inter -ideograph\;">Dr. Yuhong Liu is an Associate Professor in the Department o f Computer Science and Engineering at Santa Clara University. She received her B.S. and M.S. degrees from Beijing University of Posts and Telecommun ications in 2004 and 2007\, and her Ph.D. degree from the University of Rh ode Island in 2012.</p>\n<p class="MsoNormal" style="text-align: justify\; text-justify: inter-ideograph\;"><br>Her research focuses on responsible and trustworthy AI\, security and privacy in Agentic AI\, edge intelligenc e\, IoT\, and Blockchain. She has authored over 100 peer-reviewed papers a nd serves as an Associate Editor for IEEE Transactions on Circuits and Sys tems for Video Technology (TCSVT)\, IEEE Transactions on Service Computing (TSC)\, Multimedia Tools and Applications (MTAP)\, and APSIPA Transaction s on Signal and Information Processing (TSIP).<br><br>She also serves as a member of the IEEE Computer Society Board of Governors\, Chair of the Geo graphic Activities Committee\, Treasurer of the T&amp\;C Board\, an IEEE D istinguished Visitor (2022&ndash\;2024)\, and an APSIPA Distinguished Lect urer (2021&ndash\;2022).</p>\n<p class="MsoNormal" style="text-align: just ify\; text-justify: inter-ideograph\;"><br><strong><span style="font-size: 12.0pt\; line-height: 115%\;">Presentation: Agentic AI &ndash\; Powering the Next Wave of Energy Autonomy</span></strong></p>\n<h4><span style="col or: windowtext\; font-weight: normal\;">Abstract:</span></h4>\n<p class="M soNormal">The energy sector is undergoing rapid transformation\, driven by the rise of renewables\, decentralization\, and electrification. Utilitie s\, operators\, and enterprises face increasing pressure to manage complex ity\, volatility\, and ambitious sustainability goals. Agentic AI for ener gy autonomy offers a powerful paradigm by enabling autonomous\, goal-drive n agents that optimize generation\, distribution\, and consumption in real time.<br><br>Unlike traditional automation\, agentic systems are adaptive \, self-directed\, and capable of long-horizon decision-making. They can c oordinate distributed resources\, ensure grid stability\, and manage stora ge and demand response with minimal oversight. This talk explores the emer ging research landscape\, highlights opportunities\, and showcases case st udies that illustrate the potential and challenges of Agentic AI in energy systems.</p> END:VEVENT END:VCALENDAR