Author

Indra Jungjohann

h-index 1 View on Semantic Scholar

We have 2 of 7 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

2025

NoBOOM: Chemical Process Datasets for Industrial Anomaly Detection

NoBOOM is presented, the first collection of datasets for anomaly detection in real-world chemical process data, including labeled data from a running process at BASF SE, one of the world’s leading chemical companies.

Dennis Wagner, Fabian Hartung, J. Arweiler et al. · Neural Information Processin... · 2 citations

#machine learning Open access Apr 2026

Automated Batch Distillation Process Simulation for a Large Hybrid Dataset for Deep Anomaly Detection

This work augments a large, fully annotated experimental dataset for batch distillation with a corresponding simulation dataset, creating a novel hybrid dataset that provides a unique basis for simulation-to-experiment style transfer, the generation of pseudo-experimental data, and future research on deep AD methods in chemical process monitoring.

Jennifer Werner, J. Arweiler, Indra Jungjohann et al. · Computers & Chemical Eng... · 0 citations