Since my Master’s degree in Information Systems at the Humboldt University of Berlin in 2014, I have been a Ph.D. student in Energy Informatics and research associate at the Distributed Artificial Intelligence Laboratory (DAI-Lab) at the TU Berlin. There I have been coordinating and working on several research projects, investigating how digitization and AI can support the energy transition, e.g., by modeling, forecasting, and optimizing different demand-side processes such as electric vehicles, building and household loads, and renewable generation. I analyze low voltage-level smart meter data using non-Euclidean distance measures with applications in load forecasting and load profile clustering in my doctoral research. Currently, I coordinate the Application Center Smart Energy Systems at the DAI-Lab. I volunteer in the content committee of Climate Change AI to provide resources to get into the interdisciplinary topic of using AI and Machine Learning for climate change mitigation and adaptation.
PhD in Computer Science, 2021 (planned)
M.Sc. in Information Systems, 2014
Humboldt University of Berlin
B.Sc. in Information Systems, 2011
A building’s structural mass does provide inherent thermal storage capabilities. Within this work, a mathematical model of a building inertia thermal energy storage (BITES) is proposed to allow integration into optimized smart grid control for real-world applications.