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Personal profile

Artistic and research interests

Hossam H. H. Mousa received the B.Sc. and M.Sc. degrees in Electrical Power and Machines Engineering from South Valley University, Qena, Egypt, in 2017 and 2020, respectively. In 2018, he joined the Department of Electrical Engineering at the Faculty of Engineering, South Valley University, as a Teaching Assistant. From 2020 to the present, he has worked as an Assistant Lecturer. Currently, Mousa is a Visitor (Doctoral Researcher) at Department of Electrical Engineering and Automation, Aalto University. His research interests include electrical power engineering, MPPT techniques for renewable energy systems, Power systems, energy management, hosting capacity for active distribution networks, and control systems.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 7 - Affordable and Clean Energy
  • SDG 8 - Decent Work and Economic Growth
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 11 - Sustainable Cities and Communities
  • SDG 12 - Responsible Consumption and Production
  • SDG 13 - Climate Action
  • SDG 17 - Partnerships for the Goals

Education/Academic qualification

M.Sc. (Department of Electrical Engineering ), South Valley University

Award Date: 28 Sept 2020

Master's degree, Engineering and Technology, South Valley University

Award Date: 28 Sept 2020

BEng (Electrical Engineering), South Valley University

Award Date: 31 Jul 2017

Bachelor's degree, Engineering and Technology, South Valley University

Award Date: 31 Jul 2017

External positions

Assistant Lecturer, South Valley University

10 Oct 2020 → …

Teaching Assistant , South Valley University

12 Jul 20189 Oct 2020


  • Power System and High Voltage Engineering
  • MPPT
  • Renewable energy
  • Hosting Capacity
  • Machine Learning
  • Optimization and Learning


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