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@lanl @numfocus @conda-forge @h5io @pyiron @eisenforschung @materialdigital

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jan-janssen/README.md

Hi there πŸ‘‹

I am Jan, the group leader for Materials Informatics at the Max-Planck Institut for Sustainable Materials, where I apply methods from computer science including machine learning to discover novel materials. In addition, I lead the development of the pyiron workflow framework with a focus on performance, stability and standardization and maintain over 800 materials informatics related software packages on conda-forge to enable reproducible materials science.

Contributions to the pyiron project:

Name Description Documentation Conda Package
pyiron/atomistics Interfaces for atomistic simulation codes and workflows πŸ“š πŸ“¦
pyiron/executorlib Up-scale python functions for high performance computing πŸ“š πŸ“¦
pyiron/pylammpsmpi Parallel Lammps Python interface - control a mpi4py parallel LAMMPS instance from a serial python process or a Jupyter notebook πŸ“š πŸ“¦
pyiron/pyiron_meltingpoint A fully automated approach to determine the melting temperature of crystalline unary materials using the interface method πŸ“š
pyiron/pysqa Simple HPC queuing system adapter for Python on based jinja templates to automate the submission script creation πŸ“š πŸ“¦

Tutorials and Supplementary Information for Lectures:

Name Description Documentation Conda Package
LangSim Large Language Model (LLM) agents for atomistic simulations in computational materials science πŸ“š
SusMet Lecture Supplementary Information for the Lecture on Density Functional Theory πŸ“š

Contributions to open-source projects during my Postdoc at Los Alamos National Lab:

Name Description Documentation Conda Package
lanl/architector A 3D chemical structure generation software package designed to take minimal 2D information about ligands and metal centers and generates chemically sensible 3D conformers and stereochemistry of the organometallic compounds πŸ“¦
FitSNAP/FitSNAP Software for generating SNAP machine-learning interatomic potentials πŸ“š πŸ“¦
lanl/hippynn A modular library for atomistic machine learning with pytorch πŸ“š πŸ“¦

Contributions to the conda-forge community

Name Description Documentation Conda Package
conda-forge-contribution A template repository to gather the packages a given Github user contributed to the conda-forge community
shared-conda-environment A template repository to build conda environments using Github Actions for sharing with multiple users or to setup the same environment on multiple computers
pyiron/conda_subprocess Run a subprocess or python function in a separate conda environment πŸ“¦

Personal (non scientific) projects:

Name Description Documentation Conda Package
gmailsorter Similarity based email sorting for Google Mail using RandomForest classifiers πŸ“š πŸ“¦
pyauthenticator Similar to the Google authenticator just written in Python to automate annoying two factor authentication πŸ“¦
pymov2gif Convert *.mov files from Mac OS X screen recordings to *.gif files for uploading on Github πŸ“¦

Pinned Loading

  1. pyiron/pyiron pyiron/pyiron Public

    pyiron - an integrated development environment (IDE) for computational materials science.

    Jupyter Notebook 365 49

  2. FitSNAP/FitSNAP FitSNAP/FitSNAP Public

    Software for generating machine-learning interatomic potentials for LAMMPS

    Python 151 56

  3. LangSim LangSim Public

    Application of Large Language Models (LLM) for computational materials science - visit jan-janssen.com/LangSim

    Jupyter Notebook 55 12

  4. gmailsorter gmailsorter Public

    Similarity based email sorting for Google Mail using RandomForest classifiers

    Python 13 1

  5. conda-forge-contribution conda-forge-contribution Public template

    My contributions to the conda-forge community - over 900 packages with a total of over 250 million downloads and approximately 300 000 downloads per day - primarily focused on materials informatics.

    HTML 10 9

  6. pyauthenticator pyauthenticator Public

    Similar to the Google authenticator just written in Python to automate annoying two factor authentication.

    Python 9 1