Optimal experimental design for parameter identification and model selection - René Schenkendorf (2014)

Model-based optimization of biopharmaceutical manufacturing in Pichia pastoris based on dynamic flux balance analysis. - Victor N. Emenike; René Schenkendorf; Ulrike Krewer (Comput. Chem. Eng., 2018)

Robust dynamic optimization of enzyme-catalyzed carboligation: A point estimate-based back-off approach. - Victor N. Emenike; Xiangzhong Xie; René Schenkendorf; Antje C. Spiess; Ulrike Krewer (Comput. Chem. Eng., 2019)

An efficient polynomial chaos expansion strategy for active fault identification of chemical processes. - René Schenkendorf; Xiangzhong Xie; Ulrike Krewer (Comput. Chem. Eng., 2019)

Stochastic back-off-based robust process design for continuous crystallization of ibuprofen. - Xiangzhong Xie; René Schenkendorf (Comput. Chem. Eng., 2019)

Efficient sensitivity analysis and interpretation of parameter correlations in chemical engineering. - Xiangzhong Xie; René Schenkendorf; Ulrike Krewer (Reliab. Eng. Syst. Saf., 2019)

Global Sensitivity Methods for Design of Experiments in Lithium-ion Battery Context. - Andrea Pozzi; Xiangzhong Xie; Davide Martino Raimondo; René Schenkendorf (CoRR, 2020)

Entwicklung interdisziplinärer Module in der Hochschulbildung. - Stefanie Krause; Simon Adler; Johannes Bühl; René Schenkendorf; Kerstin Schneider; Frieder Stolzenburg; Fabian Transchel (GI-Jahrestagung, 2023)