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Muhammad Paend Bakht

Post-Doctoral Fellow – Renewable Energy

Research Interests

  • Renewable energy integration in agriculture
  • Energy economics & policy in agriculture
  • Techno-economic and environmental assessment of renewable energy systems
  • Machine Learning Applications in Energy

Current Projects

Engagement Levels of Farming Sector in Renewable Energy and Bioeconomy Projects: Balancing Economic and Environmental Sustainability funded by SEAI

Education

  • PhD, University of Technology Malaysia, Electrical Engineering.
  • MSc Engineering BUITEMS, Telecommunication Engineering
  • BSc Engineering, COMSATS University, Electrical Engineering

Professional Membership

  • Institute of Electrical and Electronics Engineers (IEEE)
  • Pakistan Engineering Council (PEC)
  • Climate-Smart Agriculture: A Path to Sustainable Food Production, 26 November 2024, Kabul University Afghanistan 
  • Optimizing Microgrid Efficiency with Interpolation and Resampling Techniques for Enhanced Machine Learning Performance, 24 July 2024, Southampton University Malaysia
  • Applications of AI in Medical Research: From Diagnostic and Treatment Optimization to Personalized Medicines, 24 January 2024, Saveetha Engineering College India
  • Application of Machine Learning to Forecast Solar Photovoltaic Output Power, 28 August 2023, University of Tun Hussein Onn Malaysia
  • Impact of electric vehicles and photovoltaic systems on power grids: A comprehensive survey, 16 November 2023, Maldives National University
  • Hybrid Energy Systems: A Pathway from Conventional to Sustainable Power Generation, 5 December 2023, University of Science Malaysia
  • Optimal Microgrids: Signal Processing and Machine Learning Applications, 30 May 2023, University of Technology Malaysia
  • A solution to mitigate load shedding problem using hybrid energy system: Case study of Pakistan, 30 July 2022, Curtin University Malaysia

I currently do not have students at Teagasc; however, I have supervised an undergraduate project titled "An IoT-Based Solar Panel PV Monitoring System Powered by Machine Learning for Enhanced Solar PV Prediction" at the University of Tun Hussein Onn Malaysia. Additionally, I have had the privilege of delivering various undergraduate-level courses in Electrical, Telecommunication, and Electronic Engineering at BUITEMS, Pakistan.