AI and Machine Learning for Energy Equity and Demand-Side Management

#IEEEPESDay #PES #AI #Nigeria #Maharashtra #India #EnergyEquity #IEEER10AIPSCC #FUTOSB #power #energy
Share

⚡️🔋💡IEEE PES Day 2026 💚

FUTO SB (Nigeria 🇳🇬 Section) x Maharashtra 🇮🇳 x Region 10 AIPSCC Collaboration Webinar 

 

Topic: AI and Machine Learning for Energy Equity and Demand side Management

Tech Speaker: Peter

Futo PES Chair: Victor

Moderator: Osuji

R10 AIPSCC Rep: Kirtiraj

Networking Beyond Boundaries 💙🎉

In celebration of the IEEE PES DAY, we are hosting this webinar to educate students on today’s Artificial Intelligence and Machine Learning are revolutionizing Demand-Side Management, intelligently shifting energy use to match supply, reduce waste, lower bills, and bring clean, stable power to everyone.


  Date and Time

  Location

  Hosts

  Registration


  • Add_To_Calendar_icon Add Event to Calendar

Loading virtual attendance info...

  • Contact Event Hosts

  • 1) IEEE R10 AIPSCC (Representative) - kirtirajgarud@ieee.org

    2) IEEE Maharashtra Section - drsameersn@ieee.org

  • Co-sponsored by AIPSCC - Artificial Intelligence for Power Systems Global Coordination committee
  • Starts 31 March 2026 11:00 PM UTC
  • Ends 23 April 2026 11:02 PM UTC
  • No Admission Charge

  Speakers

Peter Pious

Topic:

AI and Machine Learning for Energy Equity and Demand-Side Management

Discovery on how today’s Artificial Intelligence and Machine Learning are revolutionizing Demand-Side Management, intelligently shifting energy use to match supply, reduce waste, lower bills, and bring clean, stable power to everyone.

Biography:

Peter Pious Kwasi is an Electrical/Electronic Engineering professional who completed his studies at Takoradi Technical University, specializing in Instrumentation and Process Control. He currently serves as a Research Assistant at the Software and Research Hub in Ghana-Takoradi, where he is actively involved in AI/ML experiments, applied engineering research, and technical documentation.

His hands-on industrial experience spans power and oil & gas environments, having worked with control systems and instrumentation at the Volta River Authority (VRA) Aboadze Thermal Power Station and the Jubilee Technical Training Centre. Peter has undertaken both independent and collaborative research in areas such as predictive maintenance, radio frequency signal classification using machine learning, and AI-enhanced digital twin systems for autonomous control. He is passionate about the intersection of Artificial Intelligence and energy systems, and is dedicated to applying engineering solutions for practical, real-world impact. 




  Media

AI and Machine Learning for Energy Equity and Demand-Side Management Discovery on how today’s Artificial Intelligence and Machine Learning are revolutionizing Demand-Side Management, intelligently shifting energy use to match supply, reduce waste, lower bills, and bring clean, stable power to everyone 80.41 KiB