activity
20222026
most citedMachine learning in bioprocess development: From promise to practice

4 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

A Human-in-the-Loop Bayesian Optimization Framework for Constraint-Aware Bioprocess Development

Samuel Stricker, Claus Wirnsperger, Alessandro Butté +4

This work presents an extension to Pareto Front Guided Sampling (PFGS), a Human-in-the-Loop (HitL) Bayesian Optimization (BO) framework in which Gaussian process (GP) surrogate-der…

q-bio.OT2025

A Guide to Bayesian Optimization in Bioprocess Engineering

Maximilian Siska, Emma Pajak, Katrin Rosenthal +3

Bayesian optimization has become widely popular across various experimental sciences due to its favorable attributes: it can handle noisy data, perform well with relatively small d…

cs.CE2025

CarAT: Carbon Atom Tracing across Industrial Chemical Value Chains via Chemistry Language Models

Emma Pajak, David Walz, Olga Walz +3

The chemical industry is increasingly prioritising sustainability, with a focus on reducing carbon footprints to achieve net zero. By 2026, the Together for Sustainability (TfS) co…

q-bio.QM2025

Multi-fidelity batch Bayesian optimization for bioprocess development across scales

Adrian Martens, Mathias Neufang, Alessandro Butté +3

Bioprocesses are central to modern biotechnology, enabling sustainable production of pharmaceuticals, specialty chemicals, cosmetics, and food. However, developing high-performing…

cs.LG2022★ 4 cited

Machine learning in bioprocess development: From promise to practice

Laura Marie Helleckes, Johannes Hemmerich, Wolfgang Wiechert +2

Fostered by novel analytical techniques, digitalization and automation, modern bioprocess development provides high amounts of heterogeneous experimental data, containing valuable…