About

Hi there! My name is Andre Weiner. I am a research scientist working on computational fluid dynamics (CFD) and machine learning (ML). Besides ML and CFD, I am also interested in making research reproducible by employing containerization and version control (Docker, Singularity, Git, Github). Reproducibility also implies full transparency regarding source code and workflows, which is why my work as well as the work of students I supervise is available on Github. I am also an advocate for self-determined, lifelong learning.

That’s me in 2017.

Profile pages

If you are interested in my academic curriculum, have a look at the following profile pages:

• Google Scholar (journal articles)
• Technical University of Braunschweig (May 2020 - today)
• Technical University of Darmstadt (Oct 2014 - Apr 2020)

Scientific software packages

• flowTorch - a Python library for analysis and reduced-order modeling of fluid flows, Github

University courses

• Machine learning in computational fluid dynamics, TU Braunschweig, winter term 2021/2022; I designed this course from scratch; lecture notes, slides, exercises, and datasets are freely available

Presentation and training slides

• Active flow control via deep reinforcement learning implemented in OpenFOAM, OpenFOAM combustion seminar - invited talk, May 2022, Singapore, virtual
• Simulation and modal analysis of transonic shock buffets on a NACA-0012 airfoil, Euromech Colloquium 612, Mar 2022, Aachen, virtual
• Machine learning in computational fluid dynamics - an overview, keynote lecture chemical industry, Feb 2022
• Simulation and modal analysis of transonic shock buffets on a NACA-0012 airfoil, AIAA SciTech Forum, Jan 2022, San Diego, virtual
• Active control of the flow past a cylinder using deep reinforcement learning, OpenFOAM conference, Oct 2021, virtual
• flowTorch - A platform for analysis and reduced-order modeling of high-speed stall flow phenomena, DLRK 2021, Aug 2021, Bremen, virtual
• Machine learning-aided CFD with OpenFOAM and PyTorch, training at 16th OpenFOAM Workshop, Jun 2021, Dublin, virtual
• Machine learning-aided CFD with OpenFOAM and PyTorch, SSD Seminar - invited talk, Jun 2021, RWTH Aachen, virtual
• Sparse Spatial Samling - S³, AIAA SciTech Forum, Jan 2021, Nashville, virtual
• Creating data-driven workflows with OpenFOAM and PyTorch, 8th ESI OpenFOAM conference, Oct 2020, Berlin, virtual
• An introduction to supervised learning by example: path regime classification, internal training, Aug 2020, Braunschweig, virtual
• A hybrid approach to compute convection-dominated mass transfer at rising bubbles, 4th GOFUN, Apr 2020, Braunschweig, virtual
• Modeling and simulation of convection-dominated species transfer at rising bubbles, Ph.D. defense, Jan 2020, Darmstadt
• A brief introduction to machine learning and its potential application to CFD, 14th OpenFOAM workshop, Jul 2019, Duisburg
• Data-driven subgrid-scale modeling for convection-dominated concentration boundary layers, 14th OpenFOAM workshop, Jul 2019, Duisburg

Supervised student projects

• Model-based reinforcement learning for accelerated learning from CFD simulations, course project, Jan Erik Schulze, 2022, Github
• Reduced-order modeling based on cluster-based network modeling applied to the latent variables of an autoencoder, course project, Niels Formella, 2021, Github
• Active control of the flow past a cylinder under Reynolds number variation using deep reinforcement learning, Bachelor thesis, Fabian Gabriel, 2021, Github
• Numerical investigation of 2D transonic shock-buffet around a NACA 0012-34 airfoil using OpenFOAM and flowTorch, course project, Tushar Anil Gholap, 2021, Github
• Active flow control in simulations of fluid flows based on deep reinforcement learning, course project, Darshan Thummar, 2021, Github
• Simulation of Fluid Flows based on the Data-driven Evolution of Vortex Particles, Master thesis, Vemburaj Chockalingam Yadav, 2021, Github
• Datenbasierte Subgridskalen-Modellierung reaktiver Konzentrationsgrenzschichten an freiaufsteigenden Einzelblasen, Master thesis, Alexander Kiefer, 2020
• A comparative study of different mesh types for transport processes near gas bubbles regarding accuracy, stability, and run time, Bachelor thesis, Jan-Alexander Kleikemper, 2018
• Numerical simulation of single rising bubbles influenced by soluble surfactant in the spherical and ellipsoidal regime, Master thesis, Matthias Steinhausen, 2018
• Numerical simulation of reactive species transfer at a spherical gas bubble, Bachelor thesis, Tim Jeremy Patrick Karpowski, 2017