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Basics
| Name | Robert J. Flassig |
| Label | Professor (W2) of Technical Energy Efficiency |
| Url | https://www.th-brandenburg.de/ |
| Summary | Professor (W2, tenured) of Technical Energy Efficiency at Brandenburg University of Applied Sciences (THB). Since 2022, Research Professor. Research focus: data-driven and physics-informed modeling (Icing, DMD/POD/Koopman, PIKANNs), system identification and control, uncertainty quantification and explainable AI, HPC workflows for large-scale data, and applications in energy and turbomachinery systems. |
Work
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2023.05 - Present Professor (W2) for Technical Energy Efficiency — tenured
Brandenburg University of Applied Sciences (THB)
Teaching and research in energy efficiency, mathematical optimization, data-driven reduction/identification, and HPC workflows. Member of the Ethics Commission and Chair of the Examination Committee (since 2025).
- Research professorship since 2022
- Dean of Studies, MSc Energy Efficiency of Technical Systems (2020/21–04/2025)
- Program Advisor B.Sc. Mechanical Engineering (2018–2023)
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2018.05 - 2023.04 Professor (W2) for Technical Energy Efficiency — fixed-term
Brandenburg University of Applied Sciences (THB)
Developed teaching formats (DE/EN) with project and practice orientation. Engaged in third-party funding and transfer activities.
- Member of Faculty Council (2020–2021; since 2024, 26th Council)
- Member of the Ethics Commission (since 2020)
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2015.01 - 2018.04 Team Leader
Max Planck Institute for Dynamics of Complex Technical Systems (MPI-DCTS), Magdeburg
Led a research group on data-driven modeling, systems biology, and process engineering applications.
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2012.09 - 2014.12 Research Associate & Doctoral Candidate
Max Planck Institute for Dynamics of Complex Technical Systems (MPI-DCTS), Magdeburg
Research on statistical model identification and large-scale networks.
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2009.09 - 2012.08 Research Associate & Doctoral Candidate
Otto von Guericke University Magdeburg
Research as part of doctoral studies (Dr.-Ing.).
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2009.02 - 2009.08 Research Associate
Max Planck Institute for Dynamics of Complex Technical Systems (MPI-DCTS), Magdeburg
Research activity prior to starting doctoral studies.
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2006.07 - 2008.08 Working Student
Rolls-Royce Deutschland Ltd & Co KG, Dahlewitz
Industrial experience in turbomachinery.
Education
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2009.09 - 2014.04 Magdeburg, Germany
Dr.-Ing.
Otto von Guericke University Magdeburg
Process Engineering / Systems Biology (Dissertation)
- Statistical Model Identification: Dynamical Processes and Large-Scale Networks in Systems Biology
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2005.09 - 2008.09 Potsdam, Germany
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2002.10 - 2004.08 Potsdam, Germany
Awards
- 2017.01.01
DECHEMA Young Faculty Award – Digitalization in Teaching and Research
DECHEMA
Awarded for innovations in digital teaching and research.
- 2013.01.01
SBV Improver Species Translation Sub-Challenge 2 – 1st place
SBV Improver
First place in an international modeling challenge.
- 2009.01.01
DREAM 4 – 3rd place
DREAM Challenges
Top-3 placement in a systems biology and network inference benchmarking challenge.
Skills
| Data-driven Reduction & Identification | |
| DMD/POD | |
| Koopman | |
| Online Identification | |
| Validation | |
| Uncertainty Quantification |
| Physics-informed & Hybrid Models | |
| PIKANNs | |
| Thermal/Flow & Structural Coupling | |
| Icing & Shedding | |
| Heat/Mass Transport |
| HPC Workflows & Scalable Data Pipelines | |
| in-situ/in-transit analysis | |
| ADIOS2 | |
| ParaView/Catalyst2 | |
| VTK/VTU | |
| FlowTorch | |
| Gaussian Splatting |
| Statistics / ML / XAI | |
| Supervised/Unsupervised Learning | |
| Surrogate Modeling | |
| Sensitivity Analysis | |
| Explainability (XAI) | |
| UQ |
| Programming & Reproducibility | |
| Python (NumPy, SciPy, Pandas, Matplotlib, PyTorch) | |
| C/C++ | |
| Git/GitHub | |
| Conda | |
| Docker/Apptainer | |
| HPC |
Languages
| German | |
| Native speaker |
| English | |
| Professional fluency (teaching/publications) |
| French | |
| Working proficiency – suitable for professional conversations |
Projects
- 2022.01 - Present
VITVI – Virtual Engine Development with AI Methods
Team leader/supervision of 5 PhD students; research on XAI in engineering, ML-based icing models, data compression/reconstruction (including VR). Partners: TH Brandenburg, TU Berlin, BTU Cottbus-Senftenberg, Friendship Systems AG, Rolls-Royce Deutschland.
- EFRE / State of Brandenburg funding
- Icing models & VR
- XAI/UQ for engineering
- 2020.01 - 2022.12
GREEN – Holistic Solutions for an Accelerated Energy Transition
Project leader (2020–2022) for integrated solutions in energy transition.
- ESIF-funded
- System integration
- 2017.01 - 2019.12
EMIBEX
Co-applicant & project leader (2017–2019) with HS Anhalt, Fraunhofer CBP Leuna, MPI Magdeburg.
- ESIF-funded
- Industry & research consortium