Angelina Ramona Rubow

I am an Industrial PhD candidate at the Division of Applied Thermodynamics and Refrigeration at the Department of Energy Technology, specialising in bridging the gap between theoretical AI methods and their practical application in the energy sector. The research is conducted in collaboration with E1 Management Consulting GmbH.

My PhD project investigates how AI and machine learning methods can be transferred from theoretical and experimental settings into real-world energy system applications. A central objective is to address the AI “innovation gap” by analysing existing approaches, identifying implementation barriers, and developing application-oriented models together with industry stakeholders.

The research spans use cases such as asset management, predictive maintenance, operational decision support, and data-driven planning, with particular attention to data requirements, implementation constraints, and the economic implications of AI adoption in energy industry contexts.

My academic background includes an MSc in Sustainable Energy Engineering at KTH, with specialisation in Energy in Buildings and Cities. The master’s thesis examined machine learning-based electricity demand forecasting and its economic implications for German municipal utilities under current data availability.

Earlier studies include a BEng in Energy Engineering at Hochschule Flensburg (Germany), with a focus on Energy and Environmental Management and work on industrial waste heat utilisation using heat pump technology.

In parallel with doctoral research, professional work is carried out in energy industry consulting.

The supervision is provided by Prof. Hatef Madani and Dr. Nelson Sommerfeldt.