BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Lisbon BEGIN:DAYLIGHT DTSTART:20260329T020000 TZOFFSETFROM:+0000 TZOFFSETTO:+0100 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:WEST END:DAYLIGHT BEGIN:STANDARD DTSTART:20261025T010000 TZOFFSETFROM:+0100 TZOFFSETTO:+0000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:WET END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260514T063230Z UID:282A1B9A-553E-46B8-938D-6AE75EBF8A4A DTSTART;TZID=Europe/Lisbon:20260513T170000 DTEND;TZID=Europe/Lisbon:20260513T190000 DESCRIPTION:Dear Members\,\n\nWe are pleased to announce the webinar from D r. Ricardo Bessa from INESC TEC.\n\nThis webinar explores the potential an d challenges of applying foundation models to power grid operation. It int roduces the core concepts behind foundation models\, with a particular foc us on transformer-based architectures\, and discusses how to identify and select promising use cases. Key challenges related to data availability\, sharing\, and governance are also examined\, as these are critical to unlo cking the full potential of such models. In addition\, the talk highlights emerging AI paradigms that take a complementary approach: rather than rel ying solely on large-scale general knowledge\, they integrate domain exper tise with data. In this context\, neuro-symbolic learning architectures ar e presented as a promising direction for combining expert knowledge with d ata-driven methods in power system applications.\n\nRicardo Bessa (b. 1983 \, Viseu)\, IEEE Fellow\, earned his 5-years in Electrical and Computer En gineering (2006)\, M.Sc. in Data Analysis (2008)\, and Ph.D. in Sustainabl e Energy Systems (2013) from the University of Porto. He coordinates the C enter for Power and Energy Systems at INESC TEC. His research spans energy forecasting\, computational intelligence\, and smart grids. He led projec ts like AI4REALNET and contributed to FP6 ANEMOS.plus\, H2020 Smart4RES an d H2020 InteGrid. Received the ESIG (Energy Systems Integration Group) Exc ellence Award (2022) for its contributions to renewable energy forecasting .\n\nThe webinar will be held virtually on the 13th of May 2026\, from 17h to 18h30 (Portuguese time). This event will be held through ZOOM Platform . Use the following link to register:\n\nhttps://tecnico-pt.zoom.us/meetin g/register/sNgN0GluTn2Xm_jgQq7Lhg\n\nSpeaker(s): Ricardo Bessa\n\nAgenda: \n\n\nVirtual: https://events.vtools.ieee.org/m/555368 LOCATION:Virtual: https://events.vtools.ieee.org/m/555368 ORGANIZER:ch.pes@ieee-pt.org SEQUENCE:15 SUMMARY:Webinar - Applying Foundation Models to Power Grids and Emerging AI Paradigms URL;VALUE=URI:https://events.vtools.ieee.org/m/555368 X-ALT-DESC:Description: <br /><p>Dear Members\,</p>\n<p>We are pleased to a nnounce the webinar from <strong>Dr. Ricardo Bessa </strong>from <strong>I NESC TEC.</strong></p>\n<p><span lang="EN-GB" style="font-size: 12.0pt\; l ine-height: 115%\; font-family: 'Aptos'\,sans-serif\; mso-ascii-theme-font : minor-latin\; mso-fareast-font-family: Aptos\; mso-fareast-theme-font: m inor-latin\; mso-hansi-theme-font: minor-latin\; mso-bidi-font-family: 'Ti mes New Roman'\; mso-bidi-theme-font: minor-bidi\; mso-ansi-language: EN-G B\; mso-fareast-language: EN-US\; mso-bidi-language: AR-SA\;">This webinar explores the potential and challenges of applying foundation models to po wer grid operation. It introduces the core concepts behind foundation mode ls\, with a particular focus on transformer-based architectures\, and disc usses how to identify and select promising use cases. Key challenges relat ed to data availability\, sharing\, and governance are also examined\, as these are critical to unlocking the full potential of such models. In addi tion\, the talk highlights emerging AI paradigms that take a complementary approach: rather than relying solely on large-scale general knowledge\, t hey integrate domain expertise with data. In this context\, neuro-symbolic learning architectures are presented as a promising direction for combini ng expert knowledge with data-driven methods in power system applications. </span></p>\n<p><span lang="EN-GB" style="font-size: 12.0pt\; line-height: 115%\; font-family: 'Aptos'\,sans-serif\; mso-ascii-theme-font: minor-lat in\; mso-fareast-font-family: Aptos\; mso-fareast-theme-font: minor-latin\ ; mso-hansi-theme-font: minor-latin\; mso-bidi-font-family: 'Times New Rom an'\; mso-bidi-theme-font: minor-bidi\; mso-ansi-language: EN-GB\; mso-far east-language: EN-US\; mso-bidi-language: AR-SA\;">Ricardo Bessa (b. 1983\ , Viseu)\, IEEE Fellow\, earned his 5-years in Electrical and Computer Eng ineering (2006)\, M.Sc. in Data Analysis (2008)\, and Ph.D. in Sustainable Energy Systems (2013) from the University of Porto. He coordinates the Ce nter for Power and Energy Systems at INESC TEC. His research spans energy forecasting\, computational intelligence\, and smart grids. He led project s like AI4REALNET and contributed to FP6 ANEMOS.plus\, H2020 Smart4RES and H2020 InteGrid. Received the ESIG (Energy Systems Integration Group) Exce llence Award (2022) for its contributions to renewable energy forecasting. </span></p>\n<p>The webinar will be held virtually on the&nbsp\;<strong>13 th of May 2026</strong>\, from&nbsp\;<strong>17h to 18h30</strong>&nbsp\;( <strong>Portuguese time</strong>). This event will be held through ZOOM Pl atform. Use the following link to register:</p>\n<p><a href="https://tecni co-pt.zoom.us/meeting/register/sNgN0GluTn2Xm_jgQq7Lhg">https://tecnico-pt. zoom.us/meeting/register/sNgN0GluTn2Xm_jgQq7Lhg</a></p>\n<p>&nbsp\;</p>\n< p><img src="https://events.vtools.ieee.org/vtools_ui/media/display/e4f4df4 3-fd8b-4241-b91b-1bd1e7b4c3bc" width="531" height="354"></p>\n<p>&nbsp\;</ p>\n<p class="MsoNormal" style="mso-margin-top-alt: auto\; mso-margin-bott om-alt: auto\; margin-left: 3.0pt\; line-height: normal\;">&nbsp\;</p><br /><br />Agenda: <br /><p class="MsoNormal" style="mso-margin-top-alt: auto \; mso-margin-bottom-alt: auto\; line-height: normal\;">&nbsp\;</p>\n<p cl ass="MsoListParagraphCxSpLast" style="text-align: justify\; text-indent: - 18.0pt\; mso-list: l0 level1 lfo1\;">&nbsp\;</p> END:VEVENT END:VCALENDAR