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print('Howdy, Universe!')

I'm a postdoctoral researcher in the Computational Engineering lab at Empa 🇨🇭. In my research, I combine machine learning and data-driven modeling with fluid dynamics. I develop tools and algorithms that help understand high-dimensional datasets and model high-dimensional systems with computational efficiency.

Would you like to support my efforts in creating open-source science and education? You can now make a small donation of €3 on buymeacoffee.com/kamilazdybal or become a member for €3/month. My supporters gain access to extra materials on being a researcher, making effective graphics, academic writing, and being a life-long learner! Many thanks for your support! 🚀

Ongoing projects:

► I create YouTube tutorials called Python for Academics where I teach how to automate your daily academic life. Check out 🎓 this repository for a bunch of Jupyter notebooks and Python scripts helpful in your academic adventure!

► I contribute to developing PCAfold, an open-source Python library for generating, analyzing and improving low-dimensional manifolds. Check out our SoftwareX publication and check out the tutorial videos on PCAfold.

► I develop multipy, an educational Python library intended to support your learning of multicomponent mass transfer.

News:

► Check out the recent interview with me!

► My Ph.D. work has just been awarded the 18th ERCOFTAC da Vinci prize! My Ph.D. dissertation is freely available here: Reduced-order modeling of turbulent reacting flows using data-driven approaches.

► Our new paper Improving reduced-order models through nonlinear decoding of projection-dependent outputs is out in the journal Patterns from Cell Press!


Keep calm and $\frac{\partial \rho Y_i}{\partial t} = - \nabla \cdot (\rho Y_i \mathbf{v}) - \nabla \cdot \mathbf{j}_i + \omega_i$!

Kamila Zdybał's Projects

linear-algebra icon linear-algebra

This repository contains linear algebra code and learning materials.

local-manifold-learning icon local-manifold-learning

Code and materials for the "Local manifold learning and its link to domain-based physics knowledge" paper.

multipy icon multipy

multipy: Python library for multicomponent mass transfer

neural-networks icon neural-networks

Code snippets and coding tutorials for setting up non-standard neural network features.

nonlinear-decoding icon nonlinear-decoding

Code and materials for the paper "Improving reduced-order models through nonlinear decoding of projection-dependent outputs".

objectif-morse icon objectif-morse

Objectif Morse is an Arduino and C++ based project for transmitting messages in Morse alphabet. This work has been produced as part of the Arduino Study Group meetings at the Jagiellonian University.

pcafold icon pcafold

Low-dimensional PCA-derived manifolds and everything in between!

phd-dissertation icon phd-dissertation

Code and materials for my PhD dissertation: Reduced-order modeling of turbulent reacting flows using data-driven approaches

pod-dmd-decompositions icon pod-dmd-decompositions

POD and DMD decomposition of data from fluid dynamics. This work has been produced during my internship at the von Karman Institute for Fluid Dynamics under supervision of Professor Miguel A. Mendez.

pyhd icon pyhd

Useful Python resources for you PhD adventure!

python-for-academics icon python-for-academics

Python for Academics is a series of coding tutorials where you will learn how to automate your everyday academic life with Python.

ulb-atm-phd icon ulb-atm-phd

Codes and documents produced during my PhD at Université libre de Bruxelles.

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