Enzo Nicolás Spotorno Bieger
Orcid: 0009-0000-2920-3125Affiliations:
- Federal University of Santa Catarina, Universidade Federal de Santa Catarina (UFSC), Software/Hardware Integration Laboratory, Florianópolis, Brazil
According to our database1,
Enzo Nicolás Spotorno Bieger authored at least 11 papers
between 2024 and 2026.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2026
A Dual-Stream Physics-Augmented Unsupervised Architecture for Runtime Embedded Vehicle Health Monitoring.
CoRR, February, 2026
Empirical Stability Analysis of Kolmogorov-Arnold Networks in Hard-Constrained Recurrent Physics-Informed Discovery.
CoRR, February, 2026
Supervised Metric Regularization Through Alternating Optimization for Multi-Regime Physics-Informed Neural Networks.
CoRR, February, 2026
White-Box Neural Ensemble for Vehicular Plasticity: Quantifying the Efficiency Cost of Symbolic Auditability in Adaptive NMPC.
CoRR, February, 2026
Position: Certifiable State Integrity in Cyber-Physical Systems - Why Modular Sovereignty Solves the Plasticity-Stability Paradox.
CoRR, January, 2026
Linking Physical Fidelity to Downstream Performance in Physics-Informed Fault Diagnosis.
IEEE Access, 2026
2025
Hard-Constrained Neural Networks with Physics-Embedded Architecture for Residual Dynamics Learning and Invariant Enforcement in Cyber-Physical Systems.
CoRR, November, 2025
Proceedings of the 2025 IEEE Wireless Communications and Networking Conference (WCNC), 2025
Embedded Operation Effort Estimation: A Machine Learning Performance-Efficiency Trade-off Analysis.
Proceedings of the XV Symposium on Computing Systems Engineering, 2025
Physics-Informed Residual-Based Anomaly Detection and Open-Set Recognition System: A Case Study on Ring Bearings.
Proceedings of the 51st Annual Conference of the IEEE Industrial Electronics Society, 2025
2024
An Analysis of LSTMs and CNNs Robustness for Early Battery End of Life Prediction on Multivariate Time Series Based on Non-Stationarity and Entropy.
Proceedings of the 29th IEEE International Conference on Emerging Technologies and Factory Automation, 2024