Erich Studerus - Lecturer Postdoctoral Researcher at University of Applied Sciences and Arts Northwestern Switzerland FHNW, Basel

Erich Studerus

Lecturer Postdoctoral Researcher at University of Applied Sciences and Arts Northwestern Switzerland FHNW, Basel

Basel, Basel-City, Switzerland

Join Prog.AI to see contacts

Summary

🤩

Rockstar

🎓

Top School

Erich Studerus is a lecturer and postdoctoral researcher in Basel with 11 years of experience at the intersection of psychological science, biostatistics and machine learning. He has led multicenter early-detection psychosis research programs and supervised students while serving as statistical advisor and grant writer, blending hands-on data management with academic leadership. Complementing his academic work, he is an active ML engineer contributing substantial back-end enhancements to the prominent mlr machine-learning framework in R, adding numerous learners and robust handling for weights and missing data. His profile reflects a rare mix of clinical research depth, advanced methodological training (PhD, habilitation track) and practical open-source software contributions that accelerate reproducible analysis in psychology and psychiatry.

11 years of coding experience

13 years of employment as a software developer

Gymnasium St. Antonius, Appenzell

Doctor of Philosophy (PhD), Psychology, summa cum laude, Doctor of Philosophy (PhD), Psychology, summa cum laude at University of Zurich

Habilitation (Venia Docendi), PSYCHOLOGY, Habilitation (Venia Docendi), PSYCHOLOGY at University of Basel

Gymnasium Marienburg, Rheineck, SG

German, English, French

Github Skills (5)

regression10

machine-learning10

classification10

r10

caret9

Programming languages (4)

RJavaScriptPythonPostScript

Github contributions (5)

mlr-org/mlr

Jul 2014 - Jan 2017

Machine Learning in R

Role in this project:

Back-end Developer / ML Engineer

Contributions:104 commits, 9 PRs, 40 pushes in 2 years 6 months

Contributions summary:Erich made substantial contributions to the `mlr-org/mlr` repository, a machine learning framework in R. They focused on expanding the framework's capabilities by adding new learners such as `regr.cforest`, `classif.plsda_caret`, `classif.glmnet`, `classif.cforest`, `regr.glmnet`, `regr.randomForestSRC`, `classif.randomForestSRC`, `classif.bartMachine`, `regr.plsr`, `regr.randomForestSRC`, `classif.lqa`. Moreover, they integrated new measures such as `bac` and updated the codebase to handle various functionalities, including weights and missing data. Their work included significant code changes and additions to existing files related to learning algorithms and measure calculations.

imbalance-correctionlearnersensemble-learningclassificationr-package

studerus/swiss_german_gemini

Jan 2025 - Feb 2025

Contributions:5 pushes in 1 month

Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.

Request Free Trial