Biography
Dr. Rui is an E3 Assistant Professor in the Department of Civil, Structural and Environmental Engineering, Trinity College Dublin. He obtained his PhD in the fields of structural reliability and probabilistic analysis, and has both academic and industry experience.
His research focusses on the assessment of the risk and resilience of critical infrastructure systems. He has large expertise in the fields of probability theory and is interested on the application of computational methodologies and digitization to enhance the resilience and risk tolerance of civil infrastructure systems. For this, he leverages his expertise in the fields of uncertainty quantification, system optimisation, probabilistic methods, machine learning and AI, or structural systems.
He has authored multiple scientific paper in the most prestigious journals of his field, including Book Chapters, and several peer-reviewed conference publications.
He is also a resilience fellow in the 4TU in the Netherlands, and also a visiting Professor at University College Dublin. In the past Rui was a visiting professor in Chang'an University in Xi'an, China, and has served as the director of a Centre for Critical Infrastructure Research (CCIR). He also held the prestigious Marie Sklodowska-Curie scholarship and has collaborated in several national and international research projects, having also completed different roles in teaching; such as, module coordination, lecturing, or supervision of students.
Publications and Further Research Outputs
Peer-Reviewed Publications
Fang Y., Min H., Wu X., Wang W., Zhao X., Martinez-Pastor B., Teixeira R., Anomaly diagnosis of connected autonomous vehicles: A survey, Information Fusion, 105, 2024
Kandiri A., Ghiasi R., Nogal M., Teixeira R., Travel time prediction for an intelligent transportation system based on a data-driven feature selection method considering temporal correlation, Transportation Engineering, 18, 2024
Teixeira R., Martinez-Pastor B., Incremental learning of parameter spaces in machine-learning based reliability analysis, Reliability Engineering and System Safety, 245, 2024
Zhao X., Fang Y., Min H., Wu X., Wang W., Teixeira R., Potential sources of sensor data anomalies for autonomous vehicles: An overview from road vehicle safety perspective, Expert Systems with Applications, 236, 2024
Fang Y., Min H., Wu X., Zhao X., Wang X., Li G., Teixeira R., Resilience-Oriented Oscillation Dampening for Connected Autonomous Vehicle Platoons, IEEE Transactions on Vehicular Technology, 73, (11), 2024, p16024 - 16040, p16024-16040
Shang Y., Nogal M., Teixeira R., Wolfert A.R.R.M., Extreme-oriented sensitivity analysis using sparse polynomial chaos expansion. Application to train"track"bridge systems, Reliability Engineering and System Safety, 243, 2024
Bakhshian E., Teixeira R., Martinez-Pastor B., A day-to-day evacuation model to maximise transport resilience under dynamic hazards, Transportation Letters, 16, (10), 2024, p1224 - 1236, p1224-1236
Lu L., Chu X., Guo A., Fang Y., Martinez-Pastor B., Teixeira R., Cross-Vehicle Federated Learning for Unsupervised Scoring of Driver Behavior Under Privacy Constraint, IEEE Internet of Things Journal, 2024
Fang Y., Min H., Wu X., Lei X., Chen S., Teixeira R., Zhao X., Toward Interpretability in Fault Diagnosis for Autonomous Vehicles: Interpretation of Sensor Data Anomalies, IEEE Sensors Journal, 23, (5), 2023, p5014 - 5027, p5014-5027
Shang Y., Nogal M., Teixeira R., Wolfert A.R.R.M., Optimal design of rail level crossings and associated transition zones using adaptive surrogate-assisted optimization, Engineering Structures, 282, 2023
Fang Y., Teixeira R., Min H., Lei X., Chen S., Zhao X., A Safety Enhancing Framework for Autonomous Vehicles with a Resilience Rationale", 7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023, 2023, p1699 - 1705, p1699-1705
Teixeira R., Martinez-Pastor B., Vucinic L., O'Connor A., Flood adaptation decision-making for vulnerable locations using expectation"quantile"investment analysis, Journal of Flood Risk Management, 16, (1), 2023
Min H., Fang Y., Wu X., Lei X., Chen S., Teixeira R., Zhu B., Zhao X., Xu Z., A fault diagnosis framework for autonomous vehicles with sensor self-diagnosis, Expert Systems with Applications, 224, 2023
Teixeira R., O'Connor A., Val D.V., Durability and Performance of Wind Turbines Under Climate Extremes, Springer Tracts in Civil Engineering, 2022, p335 - 354, p335-354
Martinez-Pastor B., Nogal M., O'Connor A., Teixeira R., Identifying critical and vulnerable links: A new approach using the Fisher information matrix, International Journal of Critical Infrastructure Protection, 39, 2022
Teixeira R., Martinez-Pastor B., Nogal M., Micu A., O'Connor A., THE ROLE OF MULTI-FIDELITY MODELLING IN ADAPTATION AND RECOVERY OF ENGINEERING SYSTEMS, Acta Polytechnica CTU Proceedings, 36, 2022, p224 - 230, p224-230
Kandiri A., Teixeira R., Nogal M., Deciding how to decide under uncertainty: A methodology map to address decision-making under uncertainty, Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future, 2022, p1882 - 1889, p1882-1889
Teixeira R., Martinez-Pastor B., Nogal M., O'Connor A., Metamodel-based metaheuristics in optimal responsive adaptation and recovery of traffic networks, Sustainable and Resilient Infrastructure, 7, (6), 2022, p756 - 774, p756-774
Teixeira, R., Martinez-Pastor, B., Nogal, M., O'Connor, A., Reliability analysis using a multi-metamodel complement-basis approach, Reliability Engineering and System Safety, 205, 2021
Martinez-Pastor, B., Nogal, M., O'Connor, A., and Teixeira, R., Transport Network Resilience: A Mapping and Sensitivity Analysis Strategy to Improve the Decision-Making Process During Extreme Weather Events, International Journal of Critical Infrastructures, 17, (4), 2021
Teixeira R., O'Connor A., Nogal M., Application of value of information theory in adaptive metamodeling for reliability assessment, Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations, 2021
Teixeira, R., Nogal, M., O'Connor, A., Adaptive approaches in metamodel-based reliability analysis: A review, Structural Safety, 89, 2021
Teixeira, R., Nogal, M., O'Connor, A., Martinez-Pastor, B., Reliability assessment with density scanned adaptive Kriging, Reliability Engineering and System Safety, 199, 2020
Rui Teixeira, Alan O'Connor, Maria Nogal, James Nichols, Antoine Dumas, Stress-cycle fatigue design with Kriging applied to offshore wind turbines, International Journal of Fatigue, 125, 2019, p454 - 467
Teixeira, R., Nogal, M., O'Connor, A., Analysis of long-term loading characterization for stress-cycle fatigue design, Wind Energy, 22, (11), 2019, p1563-1580
Rui Teixeira, Alan O'Connor, Maria Nogal, Probabilistic sensitivity analysis of offshore wind turbines using a transformed Kullback-Leibler divergence, Structural Safety, 81, (101860), 2019
Rui Teixeira, Maria Nogal, Alan O'Connor, On the calculation of offshore wind turbine load spectra for fatigue design, Mechanical Fatigue of Metals - Experimental and Simulation Perspectives, XIX International Colloquium on Mechanical Fatigue of Metals, Porto, 2018
Rui Teixeira, Maria Nogal, Alan O'Connor, On the suitability of the generalized Pareto to model extreme waves, Journal of Hydraulic Research, 2018
Rui Teixeira, Alan O'Connor, Maria Nogal , Interpolation of confidence intervals for fatigue design using a surrogate model, New Challenges in Decision Making conference (IFED2018), Lake Louise, Canada, 6-9 May, 2018
Teixeira, R., O'Connor, A., Nogal, M., Nichols, J. and Spring, M., Structural Probabilistic Assessment of Offshore Wind Turbine Operation Fatigue Based on Kriging Interpolation, European Safety and Reliability Conference (ESREL 2017), Portoroz, Slovenia, June 18-22 2017, 2017
Rui Teixeira, Alan O'Connor, Maria Nogal, James Nichols, Nandakumar Krishnan, Analysis of the design of experiments of offshore wind turbine fatigue reliability design with Kriging surfaces, ICSI2017, Funchal, Portugal, 4-7 September 2017, Structural Integrity, ScienceDirect, 2017, pp8