| An optimal sensor placement design framework for structural health monitoring using Bayes risk Y Yang, M Chadha, Z Hu, MD Todd Mechanical Systems and Signal Processing 168, 108618, 2022 | 33 | 2022 |
| A probabilistic optimal sensor design approach for structural health monitoring using risk-weighted f-divergence Y Yang, M Chadha, Z Hu, MA Vega, MD Parno, MD Todd Mechanical Systems and Signal Processing 161, 107920, 2021 | 26 | 2021 |
| Diagnosis, prognosis, and maintenance decision making for civil infrastructure: Bayesian data analytics and machine learning MA Vega, Z Hu, Y Yang, M Chadha, MD Todd Structural health monitoring based on data science techniques, 45-73, 2022 | 14 | 2022 |
| An optimal sensor design framework accounting for sensor reliability over the structural life cycle Y Yang, M Chadha, Z Hu, MD Todd Mechanical Systems and Signal Processing 202, 110673, 2023 | 9 | 2023 |
| Bayesian damage identification using strain data from lock gates Y Yang, R Madarshahian, MD Todd Dynamics of Civil Structures, Volume 2: Proceedings of the 37th IMAC, A …, 2020 | 8 | 2020 |
| Evolutionary sensor network design for structural health monitoring of structures with time-evolving damage M CHADHA, Y YANG, Z HU, MD TODD STRUCTURAL HEALTH MONITORING 2023, 2023 | 2 | 2023 |
| Optimal Sensor Placement Considering Operational Sensor Failures for Structural Health Monitoring Applications M Chadha, Y Yang, Z Hu, MD Todd Society for Experimental Mechanics Annual Conference and Exposition, 89-92, 2023 | | 2023 |
| A Kriging Surrogate Model for Structural Health Monitoring of Miter Gates in Navigation Locks Y Yang, R Madarshahian, MD Todd | | 2023 |
| Bayesian Damage Identification Using Strain Data from Lock Y Yang, R Madarshahian, MD Todd Dynamics of Civil Structures, Volume 2: Proceedings of the 37th IMAC, A …, 2019 | | 2019 |