Predicting Time-to-Failure of Plasma Etching Equipment using Machine Learning. - Anahid N. Jalali; Clemens Heistracher; Alexander Schindler; Bernhard Haslhofer; Tanja Nemeth; Robert Glawar; Wilfried Sihn; Peter De Boer (ICPHM, 2019)

Machine Learning Techniques for the Classification of Product Descriptions from Darknet Marketplaces. - Clemens Heistracher; Franck Mignet; Sven Schlarb (ICAI, 2020)

Transfer Learning Strategies for Anomaly Detection in IoT Vibration Data. - Clemens Heistracher; Anahid N. Jalali; Indu Strobl; Axel Suendermann; Sebastian Meixner; Stephanie Holly; Daniel Schall 001; Bernhard Haslhofer; Jana Kemnitz (IECON, 2021)

Minimal-Configuration Anomaly Detection for IIoT Sensors. - Clemens Heistracher; Anahid N. Jalali; Axel Suendermann; Sebastian Meixner; Daniel Schall 001; Bernhard Haslhofer; Jana Kemnitz (CoRR, 2021)

Machine Learning Methods for Health-Index Prediction in Coating Chambers. - Clemens Heistracher; Anahid N. Jalali; Jürgen Schneeweiss; Klaudia Kovacs; Catherine Laflamme; Bernhard Haslhofer (CoRR, 2022)

Smart Active Sampling to enhance Quality Assurance Efficiency. - Clemens Heistracher; Stefan Stricker; Pedro Casas; Daniel Schall 001; Jana Kemnitz (CoRR, 2022)

MobiSpaces: An Architecture for Energy-Efficient Data Spaces for Mobility Data. - Christos Doulkeridis; Georgios M. Santipantakis; Nikolaos Koutroumanis; George Makridis; Vasilis Koukos; George S. Theodoropoulos; Yannis Theodoridis; Dimosthenis Kyriazis; Pavlos Kranas; Diego Burgos; Ricardo Jiménez-Peris; Mariana M. G. Duarte; et al. (IEEE Big Data, 2023)

An Edge Deployment Framework to Scale AI in Industrial Applications. - Jana Kemnitz; Axel Weissenfeld; Leopold Schoeffl; Andreas Stiftinger; Daniel Rechberger; Bernhard Prangl; Thomas Kaufmann; Thomas Hiessl; Stephanie Holly; Clemens Heistracher; Daniel Schall 001 (ICFEC, 2023)

Should I Sample it or Not? Improving Quality Assurance Efficiency Through Smart Active Sampling. - Clemens Heistracher; Pedro Casas; Stefan Stricker; Axel Weißenfeld; Daniel Schall 001; Jana Kemnitz (IECON, 2023)

Federated Learning for Predictive Maintenance and Quality Inspection in Industrial Applications. - Viktorija Pruckovskaja; Axel Weissenfeld; Clemens Heistracher; Anita Graser; Julia Kafka; Peter Leputsch; Daniel Schall 001; Jana Kemnitz (CoRR, 2023)

Towards eXplainable AI for Mobility Data Science. - Anahid N. Jalali; Anita Graser; Clemens Heistracher (CoRR, 2023)

Federated Learning for Anomaly Detection in Maritime Movement Data. - Anita Graser; Axel Weissenfeld; Clemens Heistracher; Melitta Dragaschnig; Peter Widhalm (MDM, 2024)