TU Kaiserslautern
Paul-Ehrlich-Straße 34 / Geb. 36
D-67663 Kaiserslautern
Office: 36-410
Phone: +49 (0)631 205 5639
Email: jan.rottmayer@scicomp.uni-kl.de
Profile
I am a passionate researcher with a focus on data-driven modeling and machine learning. My research interests include surrogate modeling, surrogate-based optimization, data-driven modeling, and generative models. With a background in mechanical engineering and a strong work ethic developed through my years as a competitive swimmer, I bring a unique perspective to my research. I completed my bachelor’s studies through a dual study system with BASF, Germany’s largest chemical company, and finished my master’s studies on the topic of reduced order modeling and optimal flow control. I have also published a student project on the generation of synthetic ground penetrating radargrams using generative adversarial networks (GANs). I am proficient in programming with Python and have a growing enthusiasm for the rising popularity of Julia in my current work on surrogate-based optimization. Thank you for visiting my profile and feel free to reach out for further collaboration or inquiries.
Talks
- Gradient Enhanced Surrogate Modeling Framework for Aerodynamic Design Optimization, AIAA Scitech 2024, 12.01.2024, Orlando FL, USA.
- Multi-Fidelity Aerodynamic Design Optimization Framework using Gradient Asissted
Surrogate Modeling, EUROGEN 2023, 02.06.2023, Crete, Greece. - Trailing Edge Noise Reduction by Porous Treatment using Derivative-Free Optimization, Scientific Computing Seminar, 05.01.2023, Kaiserslautern, Germany.
- Flow Control via Reduced Order Models, Scientific Computing Seminar, 18.11.2021, Kaiserslautern, Germany.
- Reduced Order Modeling and Nonlinear System Identification Techniques for Fluid Dynamics, Scientific Computing Seminar, 22.04.2021, Kaiserslautern, Germany.
Publications
2024
Gradient Enhanced Surrogate Modeling Framework for Aerodynamic Design Optimization Journal Article
In: AIAA 2024-2670, 2024.
2023
Data-driven aerodynamic shape design with distributionally robust optimization approaches Miscellaneous
arXiv:2310.08931, 2023.
Trailing-Edge Noise Reduction using Porous Treatment and Surrogate-based Global Optimization Miscellaneous
arXiv:2301.13047, 2023.
2021
2021 11th International Workshop on Advanced Ground Penetrating Radar (IWAGPR), 2021.