1 citations · 2 across the 4 of their papers we have counts for
4 papers
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…
Model predictive control guided with optimal experimental design for pulse-based parallel cultivation
Jong Woo Kim, Niels Krausch, Judit Aizpuru +5
Optimal experimental design for parameter precision attempts to maximize the information content in experimental data for a most effective identification of parametric model. With…