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Hi there, šŸ‘‹ I am Florian!

I'm an open-source software software developer from Munich, Germany!
I currently actively develop open-source software mainly in R and Python. Before leaving academia and joining hema.to, I enjoyed researching Automated Machine Learning, Algorithmic Fairness and many other areas of machine learning. Right now, my focus is on harnessing the power of ML and flow cytometry to help better diagnose leukemias and other disease of the blood. Here you can find my current projects and research interests!

Current Projects

R I am a member of the mlr-org core-team, we develop the mlr3 ecosystem.
I have authored/contributed to the following packages:

I furthermore worked on several other software packages:

Python

  • yahpo-gym
    I am currently working on improving yahpo-gym, a toolbox for researchers in hyperparameter optimization.
    It is built using Pytorch and ONNX and allows lightweight and lightining fast access to neural network based surrogates.

Interests

I am interested in developing software that brings a tangible benefit to users and society.
I want to work in and learn more about the following areas:

  • Deep Learning on tabular data
  • Algorithmic fairness
  • Deploying ML in the real world / MLOps
  • Everything AutoML

Freelancing

If you are interested in working together, either on open source projects or on other projects, contact me!
I have worked in a freelance capacity in several different projects before and greatly enjoyed the challenges.
I am always interested in getting to know new people and tackling interesting problems.
You can reach me at [email protected].

Other Info

  • šŸŒ± Iā€™m currently learning more about MLOps concepts and using Kubernetes
  • šŸ’¬ Ask me about R, ML, HPO, One-shot Optimization and Algorithmic Fairness
  • Reach me at [email protected]
  • šŸ˜„ Pronouns: He/him

Florian's Projects

compboost icon compboost

C++ implementation and R API for componentwise boosting

defaults icon defaults

Getting an optimal set of defaults for common machine learning algorithms

fda.usc icon fda.usc

:exclamation:Ā ThisĀ isĀ aĀ read-onlyĀ mirrorĀ ofĀ theĀ CRANĀ RĀ packageĀ repository. fda.uscĀ ā€”Ā FunctionalĀ DataĀ AnalysisĀ andĀ UtilitiesĀ forĀ StatisticalĀ Computing.Ā Homepage:Ā http://www.jstatsoft.org/v51/i04/

hpobench icon hpobench

Collection of hyperparameter optimization benchmark problems

iml icon iml

iml: interpretable machine learning R package

langchain icon langchain

āš” Building applications with LLMs through composability āš”

ml_defaults icon ml_defaults

Sets of up to 32 default values for several machine-learning algorithms

mlr icon mlr

mlr: Machine Learning in R

mlr-metalearners icon mlr-metalearners

Extending mlr using several meta-learning techniques such as stacking, multioutput and multilabel ensembles

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