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DTSTART;TZID=America/New_York:20260619T190000
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DESCRIPTION:Artificial intelligence is transforming the energy sector and c
 reating new opportunities to improve reliability\, efficiency\, safety\, a
 nd decision-making across complex technical systems. At the same time\, ap
 plying AI in energy can be challenging because these systems often involve
  critical infrastructure\, complex engineering workflows\, regulatory cons
 iderations\, and a strong need for trust\, reliability\, and explainabilit
 y.\nThis talk will provide a practical overview of how AI is being applied
  in the energy sector\, with a brief focus on nuclear energy as an example
  of a safety-conscious and highly regulated field. It will cover key AI ap
 plications\, including predictive modeling\, operational analytics\, anoma
 ly detection\, technical document intelligence\, engineering decision supp
 ort\, and human-in-the-loop workflows. The session will also discuss why s
 uccessful AI adoption in energy requires more than model accuracy alone\, 
 including validation\, traceability\, explainability\, and responsible imp
 lementation. A key theme of the talk will be that AI in energy is not just
  about building advanced models\, but also about solving meaningful proble
 ms\, supporting expert decision-making\, and building reliable systems tha
 t people can use and trust. Attendees will leave with a clearer understand
 ing of how AI can support the energy sector and what considerations are ne
 eded to apply AI responsibly in critical infrastructure\nenvironments.\n\n
 Speaker(s): Sanchari\n\nAgenda: \n1. Understand major AI applications in t
 he energy sector and how they support reliability\, efficiency\, safety\, 
 and decision-making\n2. Learn how AI can be applied to use cases such as p
 redictive modeling\, operational analytics\, anomaly detection\, technical
  document intelligence\, and engineering decision support\n3. Explore how 
 nuclear energy provides an example of AI adoption in a safety-conscious\, 
 highly regulated technical field\n4. Recognize why reliability\, explainab
 ility\, traceability\, validation\, and human oversight are essential for 
 AI in critical infrastructure\n5. Understand the importance of building pr
 actical and trustworthy AI systems that align with real-world engineering 
 workflows\n6. Leave with a clearer view of how AI can contribute to modern
 ization and responsible innovation in the energy sector\n\nVirtual: https:
 //events.vtools.ieee.org/m/562942
LOCATION:Virtual: https://events.vtools.ieee.org/m/562942
ORGANIZER:sajid.h@ieee.org
SEQUENCE:14
SUMMARY:AI in the Energy Sector: Practical and Trustworthy Solutions for Cr
 itical Infrastructure
URL;VALUE=URI:https://events.vtools.ieee.org/m/562942
X-ALT-DESC:Description: <br /><p>Artificial intelligence is transforming th
 e energy sector and creating new opportunities to improve&nbsp\;reliabilit
 y\, efficiency\, safety\, and decision-making across complex technical sys
 tems. At the same&nbsp\;time\, applying AI in energy can be challenging be
 cause these systems often involve critical&nbsp\;infrastructure\, complex 
 engineering workflows\, regulatory considerations\, and a strong need for 
 trust\,&nbsp\;reliability\, and explainability.<br>This talk will provide 
 a practical overview of how AI is being applied in the energy sector\, wit
 h a brief focus on nuclear energy as an example of a safety-conscious and 
 highly regulated field. It will cover key AI applications\, including pred
 ictive modeling\, operational analytics\, anomaly detection\, technical do
 cument intelligence\, engineering decision support\, and human-in-the-loop
  workflows. The session will also discuss why successful AI adoption in en
 ergy requires more than model&nbsp\;accuracy alone\, including validation\
 , traceability\, explainability\, and responsible implementation.&nbsp\;A 
 key theme of the talk will be that AI in energy is not just about building
  advanced models\, but also&nbsp\;about solving meaningful problems\, supp
 orting expert decision-making\, and building reliable systems&nbsp\;that p
 eople can use and trust. Attendees will leave with a clearer understanding
  of how AI can support&nbsp\;the energy sector and what considerations are
  needed to apply AI responsibly in critical infrastructure<br>environments
 .</p><br /><br />Agenda: <br /><p>1. Understand major AI applications in t
 he energy sector and how they support reliability\,&nbsp\;efficiency\, saf
 ety\, and decision-making<br>2. Learn how AI can be applied to use cases s
 uch as predictive modeling\, operational analytics\,&nbsp\;anomaly detecti
 on\, technical document intelligence\, and engineering decision support<br
 >3. Explore how nuclear energy provides an example of AI adoption in a saf
 ety-conscious\, highly&nbsp\;regulated technical field<br>4. Recognize why
  reliability\, explainability\, traceability\, validation\, and human over
 sight are&nbsp\;essential for AI in critical infrastructure<br>5. Understa
 nd the importance of building practical and trustworthy AI systems that al
 ign with&nbsp\;real-world engineering workflows<br>6. Leave with a clearer
  view of how AI can contribute to modernization and responsible&nbsp\;inno
 vation in the energy sector</p>
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