Jeroen J. Jansen

According to our database, Jeroen J. Jansen authored at least 16 papers between 2004 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

Combinatorial Order Pre-processing Search (COPS): A new pre-processing strategy for large-scale interpretable data analysis in process analytical technologies.

Wilson Cardoso, Jussara V. Roque, Jeroen J. Jansen, Sin Yong Teng, Reinaldo F. Teófilo

Comput. Chem. Eng., 2025

2024

Process expert knowledge is essential in creating value from data-driven industrial soft sensors.

Tim Offermans, Ewa Szymanska, Francisco Alexandre A. Souza, Jeroen J. Jansen

Comput. Chem. Eng., 2024

2023

Contextual Mixture of Experts: Integrating Knowledge into Predictive Modeling.

Francisco Souza, Tim Offermans, Ruud Barendse, Geert J. Postma, Jeroen J. Jansen

IEEE Trans. Ind. Informatics, August, 2023

Mono/Multi-material Characterization Using Hyperspectral Images and Multi-Block Non-Negative Matrix Factorization.

Mahdiyeh Ghaffari, Gerjen H. Tinnevelt, Marcel C. P. van Eijk, Stanislav Podchezertsev, Geert J. Postma, Jeroen J. Jansen

CoRR, 2023

Systematic reduction of Hyperspectral Images for high-throughput Plastic Characterization.

Mahdiyeh Ghaffari, Mickey C. J. Lukkien, Nematollah Omidikia, Gerjen H. Tinnevelt, Marcel C. P. van Eijk, Jeroen J. Jansen

CoRR, 2023

2022

Retrospective quality by design r(QbD) for lactose production using historical process data and design of experiments.

Leonardo Galvis, Tim Offermans, Carlo G. Bertinetto, Andrea Carnoli, Emina Karamujic, Weiwei Li, Ewa Szymanska, Lutgarde M. C. Buydens, Jeroen J. Jansen

Comput. Ind., 2022

Batch Endpoint Prediction using Local Mixture of Batch Time Experts.

Francisco Souza, Tim Offermans, Jeroen J. Jansen

Proceedings of the IEEE International Conference on Metrology for Extended Reality, 2022

2021

Automatically optimizing dynamic synchronization of individual industrial process variables for statistical modelling.

Tim Offermans, Ewa Szymanska, Geert H. van Kollenburg, Lutgarde M. C. Buydens, Jeroen J. Jansen

Comput. Chem. Eng., 2021

Process PLS: Incorporating substantive knowledge into the predictive modelling of multiblock, multistep, multidimensional and multicollinear process data.

Geert H. van Kollenburg, Roel Bouman, Tim Offermans, Jan Gerretzen, Lutgarde M. C. Buydens, Henk-Jan van Manen, Jeroen J. Jansen

Comput. Chem. Eng., 2021

2020

Fusion of Mid-Wave Infrared and Long-Wave Infrared Reflectance Spectra for Quantitative Analysis of Minerals.

Feven Desta, Mike Buxton, Jeroen J. Jansen

Sensors, 2020

Synchronizing process variables in time for industrial process monitoring and control.

Tim Offermans, Ewa Szymanska, Lutgarde M. C. Buydens, Jeroen J. Jansen

Comput. Chem. Eng., 2020

Understanding chemical production processes by using PLS path model parameters as soft sensors.

Geert H. van Kollenburg, Jacoline van Es, Jan Gerretzen, Heleen Lanters, Roel Bouman, Willem Koelewijn, Anthony N. Davies, Lutgarde M. C. Buydens, Henk-Jan van Manen, Jeroen J. Jansen

Comput. Chem. Eng., 2020

2012

Generic framework for high-dimensional fixed-effects ANOVA.

Age K. Smilde, Marieke E. Timmerman, Margriet M. W. B. Hendriks, Jeroen J. Jansen, Huub C. J. Hoefsloot

Briefings Bioinform., 2012

2009

Crossfit analysis: a novel method to characterize the dynamics of induced plant responses.

Jeroen J. Jansen, Nicole M. van Dam, Huub C. J. Hoefsloot, Age K. Smilde

BMC Bioinform., 2009

2005

ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data.

Age K. Smilde, Jeroen J. Jansen, Huub C. J. Hoefsloot, Robert-Jan A. N. Lamers, Jan van der Greef, Marieke E. Timmerman

Bioinform., 2005

2004

Analysis of longitudinal metabolomics data.

Jeroen J. Jansen, Huub C. J. Hoefsloot, Hans F. M. Boelens, Jan van der Greef, Age K. Smilde

Bioinform., 2004