| AI-driven maintenance support for downhole tools and electronics operated in dynamic drilling environments L Kirschbaum, D Roman, G Singh, J Bruns, V Robu, D Flynn IEEE Access 8, 78683-78701, 2020 | 42 | 2020 |
| Failure analysis informing embedded health monitoring of electromagnetic relays L Kirschbaum, F Dinmohammadi, D Flynn, V Robu, M Pecht 2018 3rd International Conference on System Reliability and Safety (ICSRS …, 2018 | 10 | 2018 |
| Prognostics for electromagnetic relays using deep learning L Kirschbaum, V Robu, J Swingler, D Flynn IEEE Access 10, 4861-4895, 2022 | 9 | 2022 |
| Deep learning pipeline for state-of-health classification of electromagnetic relays L Kirschbaum, D Roman, V Robu, D Flynn 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE), 1-7, 2021 | 4 | 2021 |
| Comparison of PCA and Autoencoder Compression for Telemetry of Logging-While-Drilling NMR Measurements W Weinzierl, O Mohnke, L Kirschbaum, R Coman, H Thern SPWLA Annual Logging Symposium, D041S015R002, 2024 | 1 | 2024 |
| Machine Learning Pipeline for Power Electronics State of Health Assessment and Remaining Useful Life Prediction CL Kahraman, D Roman, L Kirschbaum, D Flynn, J Swingler IEEE Access, 2024 | | 2024 |
| Data-driven prognostics for critical electronic assemblies and electromechanical components LP Kirschbaum Heriot-Watt University, 2022 | | 2022 |
| Machine Learning Pipeline for Power Electronics State of Health Assessment and Remaining Useful Life Prediction DR CIVAN LEZGIN KAHRAMAN, L KIRSCHBAUM, D FLYNN | | |
