I am Phd student in physics-based deep learning in the group ofProf. Thuerey at Technical University of Munich, funded by theMunich Center of Machine Learning (MCML). My interests are differentiable numerical simulators, machine learning, automatic differentiation, and optimization theory.

👉 Check outmy website.

📺 On my YouTube channel, I create in-depth explanatory videos onMachine Learning & Simulation.

🧑‍💻 I love coding inPython,Julia andC++. Some technologies I like to use:

JAX • Scikit-Learn • TensorFlow (Probability) • Streamlit • Flask • NumPy/SciPy/Matplotlib • Dask • The C++ Standard Library • The Eigen Linear Algebra • Library in C++ • OpenFoam • OpenMP • MPI

👉 Follow me onTwitter orLinkedIn.

💬 My favorite quote: "The best time to plant a tree was 20 years ago. The second best time is now."

💵 These are organizations I donate to yearly:

• NumFOCUS: This Non-Profit supports many open source projects like Scikit-learn, NumPy, Scipy, Julia etc.
• Wikipedia: Wikipedia is amazing. Where would I be without it.

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1. machine-learning-and-simulationmachine-learning-and-simulationPublic

   All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.com/channel/UCh0P7KwJhuQ4vrzc3IRuw4Q)

   Jupyter Notebook 954 196

2. exponaxexponaxPublic

   Efficient Differentiable n-d PDE solvers in JAX.

   Jupyter Notebook 27 1

3. scientific-python-coursescientific-python-coursePublic

   Slides + Source Code + Data for an introductory course to NumPy, Matplotlib, SciPy, Scikit-Learn & TensorFlow Keras

   Jupyter Notebook 24 7

4. pdequinoxpdequinoxPublic

   Neural Emulator Architectures in JAX.

   Python 16

5. trainaxtrainaxPublic

   Training methodologies for autoregressive neural operators/emulators in JAX.

   Python 7

6. Tsunamis.jlTsunamis.jlPublic

   🌊 🌊 🌊 Parallel Shallow Water Equations Solver by Finite Volume Method and HLLE Riemann Solver in Julia.

   Julia 19 2