AutoML for Predictive Maintenance: One Tool to RUL Them All. - Tanja Tornede; Alexander Tornede; Marcel Wever; Felix Mohr; Eyke Hüllermeier (IoT Streams/ITEM@PKDD/ECML, 2020)

Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions. - Martin W. Hoffmann; Stephan Wildermuth; Ralf Gitzel; Aydin Boyaci; Jörg Gebhardt; Holger Kaul; Ido Amihai; Bodo Forg; Michael Suriyah; Thomas Leibfried; Volker Stich; Jan Hicking; et al. (Sensors, 2020)

Coevolution of remaining useful lifetime estimation pipelines for automated predictive maintenance. - Tanja Tornede; Alexander Tornede; Marcel Wever; Eyke Hüllermeier (GECCO, 2021)

Towards Green Automated Machine Learning: Status Quo and Future Directions. - Tanja Tornede; Alexander Tornede; Jonas Hanselle; Felix Mohr; Marcel Wever; Eyke Hüllermeier (J. Artif. Intell. Res., 2023)

Algorithm selection on a meta level. - Alexander Tornede; Lukas Gehring; Tanja Tornede; Marcel Wever; Eyke Hüllermeier (Mach. Learn., 2023)

PyExperimenter: Easily distribute experiments and track results. - Tanja Tornede; Alexander Tornede; Lukas Fehring; Lukas Gehring; Helena Graf; Jonas Hanselle; Felix Mohr; Marcel Wever (J. Open Source Softw., 2023)

Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning. - Joseph Giovanelli; Alexander Tornede; Tanja Tornede; Marius Lindauer (AAAI, 2024)

Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks. - Leona Hennig; Tanja Tornede; Marius Lindauer (CoRR, 2024)

AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks. - Alexander Tornede; Difan Deng; Theresa Eimer; Joseph Giovanelli; Aditya Mohan; Tim Ruhkopf; Sarah Segel; Daphne Theodorakopoulos; Tanja Tornede; Henning Wachsmuth; Marius Lindauer (Trans. Mach. Learn. Res., 2024)