Contact Bernadin Namoano
Areas of expertise
- Digital Twinning
Background
Bernadin has received his MSc degree in computer science in 2013 from Polytechnique University (France). Before joining Cranfield University in 2017, he worked as software engineer in Paris, focusing on architectural design for big data, big time series data analysis, and software lifecycle implementation and maintenance.
He completed his PhD funded by EPSRC and Unipart-rail/Instrumentel, at Cranfield University in the field of condition monitoring applied to railway assets, and was awarded the EPSRC doctoral fellowship Prize.
Current activities
Bernadin's main research areas have been the development of novel architectures and algorithms for digital twin development. He is currently working on his Research fellow Prize at the Centre of Digital Engineering and Manufacturing in Cranfield University. His work involves the design, implementation, and testing of novel methods and tools for digital twin ecosystem development.
Clients
- Siemens Energy AG
- BAE Systems PLC
- Babcock International
- Network Rail
Publications
Articles In Journals
- Wang Y, Liu H, Yang L, Durazo-Cardenas I, Namoano B, .... (2024). A full 3D reconstruction of rail tracks using a camera array. Measurement, 225
- Namoano B, Latsou C & Erkoyuncu JA. (2024). Multi-channel anomaly detection using graphical models. Journal of Intelligent Manufacturing
- Namoano B, Emmanouilidis C & Starr A. (2024). Detecting wheel slip from railway operational data through a combined wavelet, long short-term memory and neural network classification method. Engineering Applications of Artificial Intelligence, 137
- Millogo AMD, Tankoano B, Neya O, Folega F, Wala K, .... (2024). Spatiotemporal Analysis of Land Use and Land Cover Dynamics of Dinderesso and Peni Forests in Burkina Faso. Geomatics, 4(4)
- Yang M, Namoano B, Farsi M & Ahmet Erkoyuncu J. (2024). Named Entity Recognition in Aviation Products Domain Based on BERT. IEEE Access, 12
- Shimizu M, Perinpanayagam S, Namoano B & Starr A. (2023). Real-Time Prognostics and Health Management Without Run-to-Failure Data on Railway Assets. IEEE Access, 11
- Addepalli S, Weyde T, Namoano B, Oyedeji OA, Wang T, .... (2023). Automation of knowledge extraction for degradation analysis. CIRP Annals, 72(1)
- Erkoyuncu JA, Namoano B, Kozjek D & Vrabič R. (2023). Cognitive data imputation: Case study in maintenance cost estimation. CIRP Annals, 72(1)
- Shimizu M, Perinpanayagam S & Namoano B. (2022). A Real-Time Fault Detection Framework Based on Unsupervised Deep Learning for Prognostics and Health Management of Railway Assets. IEEE Access, 10
- DENG H, Namoano B, ZHENG B, Khan S & Ahmet Erkoyuncu J. From Prediction to Prescription: Large Language Model Agent for Context-Aware Maintenance Decision Support. PHM Society European Conference, 8(1)
- Durazo-Cardenas I, Namoano B, Starr A, Dilip Sala R & Lai J. False alarm reduction in railway track quality inspections using machine learning. PHM Society European Conference, 8(1)
Conference Papers
- Addepalli S, Namoano B, Oyedeji OA, Farsi M & Erkoyuncu JA. (2023). Designing a semantic based common taxonomy of mechanical component degradation to enable maintenance digitalisation
- Farsi M, Namoano B, Sonmez AN, Addepalli S & Erkoyuncu JA. (2023). A Robust Design for Lifecycle Cost with Reliability Analysis Integration
- Namoano B, Ruiz-Carcel C, Emmanouilidis C & Starr AG. (2022). Data-Driven Wheel Slip Diagnostics for Improved Railway Operations
- Shimizu M, Perinpanayagam S & Namoano B. (2022). A Fault Detection Technique based on Deep Transfer Learning from Experimental Linear Actuator to Real-World Railway Door Systems
- Shimizu M, Perinpanayagam S & Namoano B. (2022). Real-Time Techniques for Fault Detection on Railway Door Systems
- Alotaibi A, Durazo Cardenas I, Namoano B & Starr A. (2022). rack geometry deterioration modelling for asset management: A visual analytics approach
- Namoano B, Ruiz-Carcel C, Emmanouilidis C & Starr AG. (2022). Data-Driven Wheel Slip Diagnostics for Improved Railway Operations
- Namoano B, Emmanouilidis C, Ruiz-Carcel C & Starr AG. (2020). Change detection in streaming data analytics: A comparison of Bayesian online and martingale approaches
- Namoano B, Starr A, Emmanouilidis C & Cristobal RC. (2019). Online change detection techniques in time series: An overview