Maximilian Theisen is a PhD candidate in the Process Intelligence Research group. His research focuses on graph neural networks that use the process topology of a plant to learn from operational data, for example as soft sensors. A main case study is multistage spray drying with industrial data from Danone. He received his BSc in Mechanical Engineering from RWTH Aachen University, including an academic year at the University of California, Davis, and his MSc in Chemical Engineering from TU Delft.
Interests
- Chemical engineering
- Machine learning
- Optimization
- Deep Learning
Education
MSc in Chemical Engineering, 2023
Delft University of Technology
BSc in Mechanical Engineering, 2021
RWTH Aachen University