Florian Rupprecht

Building tools for science

I build compilers, graphics systems, and developer tools, mostly for scientists. Currently at the Child Mind Institute, though I'm easily distracted by interesting problems.

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Florian Rupprecht

Selected Projects

Some things I've built.

2025

Styx

Multi-language compiler that transforms command-line tool metadata into type-safe, language-native wrappers for Python, TypeScript, and R. Adopted by multiple research institutions including MIT, McGill, and Stanford.

PythonTypeScriptRCLI
Styx screenshot

Published in bioRxiv

2025

NiWrap

The largest cross-platform neuroimaging tool library, built on Styx. Provides unified Python, TypeScript, and R interfaces to 2,000+ tools across 20+ neuroimaging packages with automated container orchestration.

PythonTypeScriptRDockerNeuroimaging
NiWrap screenshot

2,000+ tool interfaces

Live demo →
2021

httpgd / unigd

Asynchronous HTTP server graphics device for R providing real-time, network-accessible scientific data visualization. Integrated into the primary R extension for Visual Studio Code and adopted by thousands of R developers worldwide.

C++RJavaScriptWebSockets

Integrated in VS Code R extension

2024

headjack

Interactive NIfTI brain image viewer for the terminal. Runs anywhere including remote clusters and containers, with no runtime dependencies.

RustTerminal

Zero-dependency binary

Experience

What keeps me busy.

July 2025 — Present
New York, US

Senior Scientific Software Developer

Child Mind Institute

Research

Providing programming support and mentorship for scientific and clinical projects. Designing scalable software pipelines, web applications, and data visualization tools for neuroimaging analysis. Leading machine learning implementation in clinical contexts while ensuring data security and compliance.

November 2022 — June 2025
New York, US

Scientific Software Developer

Child Mind Institute

Research

Integrated neuroimaging processing into Python-based pipeline frameworks and developed testing/visualization tools for brain imaging analysis. Extended processing techniques for functional and diffusion MRI datasets on HPC infrastructure while collaborating with data analysts to improve processing efficiency.

November 2021 — April 2022
Berlin, DE

Junior Outcomes Research Manager

Pfizer (Germany)

Outcomes Research

Technical consulting on data processing automation and ML infrastructure for outcomes research. Worked with global teams on statistical analysis and methodology.

July 2020 — August 2020
Radolfzell, DE

Intern

Max Planck Institute of Animal Behavior

Collective Behavior

Built real-time physics simulation framework for animal behavior experiments. Developed projection systems for controlled stimulus presentation.

Publications

Papers I've accidentally written.

3 publications • Last updated: 2/28/2026

2025
Preprint

Styx: A multi-language API Generator for Command-Line Tools

Florian Rupprecht, Jason Kai, Biraj Shrestha, Steven Giavasis, Ting Xu, Tristan Glatard, Michael P Milham, Gregory Kiar

View paper → DOI: 10.1101/2025.07.24.666435
Styx: A multi-language API Generator for Command-Line Tools figure
2022

Automating LC–MS/MS mass chromatogram quantification: Wavelet transform based peak detection and automated estimation of peak boundaries and signal-to-noise ratio using signal processing methods.

Florian Rupprecht, Soren Enge, Kornelius Schmidt, Wei Gao, Robert Miller

Biomedical Signal Processing and Control

View paper → DOI: 10.1016/j.bspc.2021.103211
Automating LC–MS/MS mass chromatogram quantification: Wavelet transform based peak detection and automated estimation of peak boundaries and signal-to-noise ratio using signal processing methods. figure
2021

How to deal with non-detectable and outlying values in biomarker research: Best practices and recommendations for univariate imputation approaches

Judith Herbers, Robert Miller, Andreas Walther, Lena Schindler, Kornelius Schmidt, Wei Gao, Florian Rupprecht

Comprehensive Psychoneuroendocrinology

View paper → DOI: 10.1016/j.cpnec.2021.100052
How to deal with non-detectable and outlying values in biomarker research: Best practices and recommendations for univariate imputation approaches figure
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Let's Build Something.

Interested in collaborating on research tools, software, or scientific infrastructure?

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