5 citations · 9 across the 9 of their papers we have counts for
9 papers
RamanBench: A Large-Scale Benchmark for Machine Learning on Raman Spectroscopy
Mario Koddenbrock, Christoph Lange, Robin Legner +6
Machine learning (ML) has transformed many scientific fields, yet key applications still lack standardized benchmarks. Raman spectroscopy, a widely used technique for non-invasive…
Automatic Raman Measurements in a High-Throughput Bioprocess Development Lab
Christoph Lange, Simon Seidel, Madeline Altmann +6
This study presents a collection of physical devices and software services that fully automate Raman spectra measurements for liquid samples within a robotic facility. This method…
Deep learning adaptive Model Predictive Control of Fed-Batch Cultivations
Niels Krausch, Martin Doff-Sotta, Mark Cannon +2
Bioprocesses are often characterised by nonlinear and uncertain dynamics, posing particular challenges for model predictive control (MPC) algorithms due to their computational dema…
Data Augmentation Scheme for Raman Spectra with Highly Correlated Annotations
Christoph Lange, Isabel Thiele, Lara Santolin +4
In biotechnology Raman Spectroscopy is rapidly gaining popularity as a process analytical technology (PAT) that measures cell densities, substrate- and product concentrations. As i…
Handling nonlinearities and uncertainties of fed-batch cultivations with difference of convex functions tube MPC
Niels Krausch, Martin Doff-Sotta, Mark Canon +2
Bioprocesses are often characterized by nonlinear and uncertain dynamics. This poses particular challenges in the context of model predictive control (MPC). Several approaches have…
Latent State Space Extension for interpretable hybrid mechanistic models
Judit Aizpuru, Maxim Borisyak, Peter Neubauer +1
Mechanistic growth models play a major role in bioprocess engineering, design, and control. Their reasonable predictive power and their high level of interpretability make them an…
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development
Nghia Duong-Trung, Stefan Born, Jong Woo Kim +9
Machine learning (ML) is becoming increasingly crucial in many fields of engineering but has not yet played out its full potential in bioprocess engineering. While experimentation…
Model predictive control and moving horizon estimation for adaptive optimal bolus feeding in high-throughput cultivation of \textit{E. coli}
Jong Woo Kim, Niels Krausch, Judit Aizpuru +4
We discuss the application of a nonlinear model predictive control (MPC) and a moving horizon estimation (MHE) to achieve an optimal operation of \textit{E. coli} fed-batch cultiva…
Fitting nonlinear models to continuous oxygen data with oscillatory signal variations via a loss based on DynamicTime Warping
Judit Aizpuru, Annina Karolin Kemmer, Jong Woo Kim +4
High throughput experimental systems play an important role in bioprocess development, as they provide an efficient way of analysing different experimental conditions and perform s…