Mr. Mousa Alizadeh
Details
Department: School of Engineering
Campus: City Campus Australia
mousa.alizadeh@rmit.edu.au
Open to
- Collaborative projects
- Industry Projects
- Join a web conference as a panellist or speaker
About
Mousa Alizadeh is a Postdoctoral Research Fellow (Level A) in the Department of Electrical and Electronic Engineering at RMIT University, working at the intersection of artificial intelligence, smart energy systems, and electrified transport. His research focuses on the planning, operation, and intelligent management of future energy infrastructure, with particular interests in electric vehicle charging, power distribution networks, energy storage, vehicle-to-grid integration, distributed energy resources, and integrated energy–transport systems. Building on a broader background in control systems, forecasting, data science, and intelligent systems, his work seeks to connect fundamental research with industry-relevant applications and practical decision-making. He has contributed to national and industry-linked research initiatives, interdisciplinary collaborations, research translation, postgraduate research development, and scholarly publication, with the broader objective of supporting reliable, flexible, and sustainable energy systems.
Selected Awards and Recognition:
- API–C4NET PhD Industry Conference Award, Energy Networks Australia Conference, 2026
- IEEE IAS AUS–NZ/R10 CMD Travel Grant, ETFG 2025
- RACE for 2030 Strategic EV Integration Industry PhD Top-Up Scholarship, 2024
- RMIT University PhD Scholarship, including tuition fee waiver and annual stipend, 2023–2026
Research fields
- 400805 Electrical energy transmission, networks and systems
- 4602 Artificial intelligence
- 460501 Data engineering and data science
- 490304 Optimisation
- 400705 Control engineering
UN sustainable development goals
- 7 Affordable and Clean Energy
- 9 Industry, Innovation and Infrastructure
- 13 Climate Action
Teaching interests
His teaching spans intelligent systems, data science, machine learning, programming, and control engineering, with experience in laboratory delivery, student assessment, project-based learning, and professional technical training. He adopts an applied, research-informed approach that connects theoretical foundations with practical problem-solving and industry-relevant applications.
Research interests
- Smart energy systems
- Artificial intelligence and machine learning
- Data-driven modelling and decision-making
- Optimisation and control of complex systems
- Electrified and sustainable infrastructure
- Energy-system planning and operation
- Industry-oriented engineering applications
