Molaioni, F., Andriotis, C.P., and Rinaldi, Z., 2025. "Life-cycle fragility analysis of aging reinforced concrete bridges: A dynamic Bayesian network approach", Structural Safety, 102654.
Jewett, J.L., Koniari, A.M., Andriotis, C.P., Oikonomopoulou, F., Bristogianni, T., and Carstensen, J.V., 2025. “More with less: topology optimization strategies for structural glass design”, Glass Structures & Engineering, 10(2), pp.1-18.
van Remmerden, J., Kenter, M., Roijers, D.M., Andriotis, C.P., Zhang, Y., Bukhsh, Z., 2025. “Deep multi-objective reinforcement learning for utility-based infrastructural maintenance optimization”, Neural Computing and Applications, pp.1-24.
Saifullah, M., Papakonstantinou, K.G., Andriotis, C.P., Stoffels, S., 2024. “Decentralized stochastic optimal inspection and maintenance control solutions in multi-asset transportation networks”, arXiv preprint arXiv:2401.12455.
Lai, L., Dong, Y., Andriotis, C.P., Wang, A., Lei, X., 2024. “Synergetic-informed deep reinforcement learning with hierarchical rewards for life-cycle sustainable management of transportation networks with large discrete action spaces”, Automation in Construction, Elsevier.
Bianchi, S., Andriotis, C.P., Klein, T., Overend, M., 2024. “Multi-criteria design methods in façade engineering: state-of-the-art and future trends”, Building and Environment, Elsevier.
Morato, P.G., Andriotis, C.P., Papakonstantinou, K.G., and Rigo, P., 2023. “Inference and dynamic decision-making for deteriorating systems with probabilistic dependencies through Bayesian networks and deep reinforcement learning”, Reliability Engineering & System Safety, 109144.
Altamimi, A.L., Lagoa, C., Borges, J., Andriotis, C.P., Papakonstantinou, K.G., 2022. “Large-scale wildfire mitigation through deep reinforcement learning”, Frontiers in Forests and Global Change, 5, 734330.
Morato, P.G., Papakonstantinou, K.G., Andriotis, C.P., Nielsen, J.S., and Rigo, P., 2022. “Optimal inspection and maintenance planning for deteriorating structural components using dynamic Bayesian networks and Markov decision processes”, Structural Safety, 94, 102140.
Andriotis, C.P., and Papakonstantinou, K.G., 2021. “Deep reinforcement learning driven inspection and maintenance planning under incomplete information and constraints”, Reliability Engineering & System Safety, 212, 107551.
Lyritsakis, C.M., Andriotis, C.P., and Papakonstantinou, K.G., 2021. “Geometrically exact hybrid beam element based on nonlinear programming”, International Journal for Numerical Methods in Engineering 122 (13), 3273-3299.
Andriotis, C.P., Papakonstantinou, K.G., and Chatzi, E.N., 2020. “Value of structural health information in partially observable stochastic environments”, Structural Safety, 93, 102072.
Andriotis, C.P., and Papakonstantinou, K.G., 2019. “Managing engineering systems with large state and action spaces through deep reinforcement learning”, Reliability Engineering & System Safety, 191 (11), 106483.
Andriotis, C.P., and Papakonstantinou, K.G., 2018. “Extended and generalized fragility functions”, Journal of Engineering Mechanics, 144 (9), 04018087.
Papakonstantinou K.G., Andriotis C.P., and Shinozuka M., 2018. “POMDP and MOMDP solutions for structural life-cycle cost minimization under partial and mixed observability”, Structure and Infrastructure Engineering, 14 (7), 869-882.
Andriotis, C.P., Papakonstantinou, K.G., and Koumousis, V.K., 2018. “Nonlinear programming hybrid beam-column element formulation for large displacement elastic and inelastic analysis”, Journal of Engineering Mechanics, 144 (10), 04018096.
Andriotis, C.P., Gkimousis, I., and Koumousis, V.K., 2016. “Modeling reinforced concrete structures using smooth plasticity and damage models”, Journal of Structural Engineering, vol. 142, no. 2, p. 04015105.
Sterrenberg, A., Andriotis, C.P., Stoter, J., 2025. “Modelling stochastic degradation and maintenance effects for the road network of Amsterdam: A multi-attribute data-driven approach”, 14th International Conference on Structural Safety and Reliability (ICOSSAR), Los Angeles, CA, USA.
Ding, X., Asut, S., Andriotis, C.P., 2025. “Closed-loop control of 3D clay printing using machine learning”,Digitalisation of the Built Environment: 4th 4TU/14UAS, Groningen, The Netherlands.
Koniari, A.M., Andriotis, C.P., Bianchi, S., Morato, P.G., Khademi, S., Overend, M., 2025. “Predicting building operational energy at urban level under material degradation and climate uncertainty: A sensitivity analysis”, 6th International Conference on Uncertainty Quantification in Computational Science and Engineering (UNCECOMP), Rhodes, Greece.
Martinez-Alcaraz, P., de la Barra, P., Andriotis, C.P., Luna-Navarro, A., 2025. “Understanding the importance of tailoring thermal conditions: A data-mining Bayesian approach”, CLIMA Conference on Decarbonized, healthy and energy conscious buildings in future climates, Milano, Italy.
Molaioni, F., Andriotis, C.P., Rinaldi, Z., 2024. “A dynamic Bayesian network approach for the multi-component fragility assessment for reinforced concrete bridges”, 12th International Conference on Bridge Maintenance, Safety and Management (IABMAS), Copenhagen, Denmark.
Metwally, Z., Andriotis, C.P., Molaioni, F., 2024. “Infrastructure management through reinforcement learning with adaptive information sharing”, 12th International Conference on Bridge Maintenance, Safety and Management (IABMAS), Copenhagen, Denmark.
Mueller, L.M., Andriotis, C.P., Turrin, M., 2024. “Generating building geometry using deep learning models: data and parameterization requirements”, 23rd Association for Computer-Aided Architectural Design Research in Asia Conference (eCAADe), Nicosia, Cyprus.
Mueller, L.M., Andriotis, C.P., Turrin, M., 2024. “Using generative adversarial networks to create 3D building geometries”, 23rd Association for Computer-Aided Architectural Design Research in Asia Conference (eCAADe), Nicosia, Cyprus.
Martinez-Alcaraz, P., de la Barra, P., Andriotis, C.P., Wang, Y., Luna-Navarro, A., 2024. “Personalized building controls based on individual thermal preferences for energy efficiency and thermal comfort”, Internation Association of Building Physics Conference (IBPC), Toronto, Canada.
Kazemi, P., Turrin, M., Andriotis, C.P., Entezami, A., Ghisi, A., Mariani, S., 2024. “Deep learning approach to structural sustainability of tall buildings in seismic areas”, International Association of Spatial Structures (IASS) Conference, Zurich, Switzerland.
Luna-Navarro, A., Khanchandani, P., Brembilla, E., de la Barra, P., Andriotis, C.P., 2023. “Towards multi-domain user archetypes for user-centred façade design”, International Scientific Conference on the Built Environment in Transition (CISBAT), Lausanne, Switzerland.
Bhustali, P., Andriotis, C.P., 2023. “Assessing the optimality of decentralized inspection and maintenance policies for stochastically degrading engineering systems”, BNAIC/BeNeLearn Joint International Scientific Conferences on AI and Machine Learning, Delft, The Netherlands.
van Rammerden, J., Kenter, M., Roijers, D., Zhang, Y., Andriotis, C.P., Bukhsh, Z., 2023. “A deep multi-objective reinforcement learning approach for infrastructural maintenance planning with non-linear utility functions”, MODeM Workshop, 26th European Conference on Artificial Intelligence (ECAI), Krakow, Poland.
Andriotis, C.P., Metwally, Z., 2023. “Structural integrity management via hierarchical resource allocation and continuous-control reinforcement learning”, 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP), Dublin, Ireland.
Saifullah, M., Andriotis C.P., Papakonstantinou, K.G., 2023. “The role of value of information in multi-agent deep reinforcement learning for optimal decision-making under uncertainty”, 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP), Dublin, Ireland.
Lathourakis, C., Andriotis, C.P., Cicirello, A., 2023. “Inference and maintenance planning of monitored structures through Markov chain Monte Carlo and deep reinforcement learning”, 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP), Dublin, Ireland.
Morato, P.G., Papakonstantinou, K.G., Andriotis, C.P., Hlaing, N., Kolios, A., 2023. “Interpretation and analysis of deep reinforcement learning driven inspection and maintenance policies for engineering systems”, 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP), Dublin, Ireland.
Koniari, A.M., Andriotis, C.P., and Oikonomopoulou, F., 2023. “Minimum mass cast glass structures under performance and manufacturability constraints”, 20th International Conference on Computer-Aided Architectural Design Futures (CAAD Futures), Delft, The Netherlands.
Molaioni, F., Rinaldi, Z., and Andriotis, C.P., 2023. “Assessing life-cycle seismic fragility of corroding reinforced concrete bridges through dynamic Bayesian networks”, 8th International Symposium on Life-Cycle Civil Engineering (IALCCE), Milan, Italy.
Hlang, N., Morato, P.G., Papakonstantinou, K.G., Andriotis, C.P., Rigo, P., 2022. “Interpretation of offshore wind management policies identified via partially observable Markov decision processes”, European Academy of Wind Energy (EAWE) PhD Seminar.
Andriotis C.P., and Papakonstantinou, K.G., 2022. “Optimizing policies for deteriorating systems using intrinsic action structuring and value of information”, 13th International Conference on Structural Safety & Reliability (ICOSSAR), Shanghai, China.
Morato, P.G., Papakonstantinou, K.G., Andriotis, C.P., and Rigo, P., 2022. “Managing off-shore wind turbines through Markov decision processes and dynamic Bayesian networks”, 13th International Conference on Structural Safety & Reliability (ICOSSAR), Shanghai, China.
Yi, S., Papakonstantinou, K.G., Andriotis, C.P., and Song, J., 2022. “Appraisal and mathematical properties of fragility analysis methods”, 13th International Conference on Structural Safety & Reliability (ICOSSAR), Shanghai, China.
Saifullah, M., Andriotis C.P., Papakonstantinou, K.G., and Stoffels, S.M., 2022. “Deep reinforcement learning-based life-cycle management of deteriorating transportation systems”, 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS), Barcelona, Spain.
Andriotis C.P., and Papakonstantinou, K.G., 2019. “Life-cycle policies for large engineering systems under complete and partial observability”, 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP), Seoul, South Korea.
Papakonstantinou, K.G., Andriotis, C.P., Gao, H., and Chatzi, E.N., 2019. “Quantifying the value of information of structural health monitoring for decision making”, 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP), Seoul, South Korea.
Lyritsakis, C.M., Andriotis C.P., and Papakonstantinou, K.G., 2019. “Nonlinear programming approach to a shear-deformable hybrid beam element for large displacement inelastic analysis”, 7th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN), Crete, Greece.
Andriotis C.P., and Papakonstantinou, K.G., 2018. “Dependent Markov models for long-term structural fragility”, 11th National Conference on Earthquake Engineering (NCEE), Los Angeles, CA, USA.
Andriotis C.P., Papakonstantinou, K.G., and Rathod, Y., 2018. “A consistent integrated formulation for fragility analysis and comparison with different methods”, 16th European Conference on Earthquake Engineering (ECEE), Thessaloniki, Greece.
Andriotis C.P., and Papakonstantinou, K.G., 2018. “Probabilistic structural performance assessment in hidden damage spaces”, Computational Stochastic Mechanics (CSM) Conference, Paros, Greece.
Andriotis C.P., and Papakonstantinou, K.G., 2017. “Generalized multivariate fragility functions with multiple damage states”, 12th International Conference on Structural Safety & Reliability (ICOSSAR), Vienna, Austria.
Papakonstantinou K.G., Andriotis C.P., and Shinozuka M., 2016. “Point-based POMDP solvers for life-cycle cost minimization of deteriorating structures”, 5th International Symposium on Life-Cycle Civil Engineering, Delft, The Netherlands.
Papakonstantinou, K.G., Andriotis C.P., and Shinozuka M., 2016. “POMDP solutions for monitored structures”, Proceedings of IFIP WG-7.5 Conference on Reliability and Optimization of Structural Systems, Pittsburgh, PA.
Andriotis, C.P., Metwally, Z., 2025. “Sequential intervention planning in multi-component engineering systems through hierarchical resource allocation”, Engineering Mechanics Institute Conference (EMI), Anaheim, CA, USA.
Morato, P.G., Andriotis, C.P., Khademi, S., 2025. “Batch Bayesian active learning under budget constraints”, Engineering Mechanics Institute Conference (EMI), Anaheim, CA, USA.
Bhustali, P., Andriotis, C.P., Morato, P.G., Papakonstantinou, K.G., 2025. “Decentralizing Decisions: A Multi-Agent Deep Reinforcement Learning Approach to Inspection and Maintenance Planning”, Engineering Mechanics Institute Conference (EMI), Anaheim, CA, USA.
Morato, P.G., Andriotis, C.P., Koniari, A.M., Khademi, S., 2025. “Efficient active learning for high-dimensional engineering analysis via Bayesian neural networks”, 14th International Conference on Structural Safety and Reliability (ICOSSAR), Los Angeles, CA, USA.
Hettegger, D., Morato, P.G., Bhustali, P., Koutas, D., Metwally, Z., Arcieri, G., Leroy, P., Hlaing, N., Bhattacharya, A., Andriotis, C.P., Papakonstantinou, K.G., Straub, D., 2025. “Benchmark environments for road network maintenance”, 14th International Conference on Structural Safety and Reliability (ICOSSAR), Los Angeles, USA.
Los, A., Andriotis, C.P., Moody, R., Khademi, S., Morato, P.G., Koniari, A.M., van Rooy, I., Steenbergen-Cockerton, H., 2025. “Data-driven building retrofit planning considering socio-economic and environmental factors”, 12th International Conference on Urban Climate (ICUC), Rotterdam, The Netherlands.
Jewett, J., Koniari, A.M., Andriotis, C.P., Oikonomopoulou, F., Bristogianni, T., Carstensen, J., 2024. “More with less: Topology optimization strategies for structural glass design”, Challenging Glass Conference, Delft, The Netherlands.
Bhustali, P., Andriotis, C.P., Morato, P.G., Papakonstantinou, K.G., 2024. “Understanding multi-agent cooperation in deep reinforcement learning for inspection and maintenance planning”, Engineering Mechanics Institute Conference (EMI), Chicago, IL, USA.
Morato, P.G., Moran, J., Koniari, A.M., Hlaing, N., Khademi, S., Andriotis, C.P., 2024. “Bayesian neural networks for active learning and uncertainty quantification with big data”, Engineering Mechanics Institute Conference (EMI), Chicago, IL, USA.
Bhustali, P., Andriotis, C.P., 2024. “Model-based reinforcement learning for optimal inspection and maintenance planning”, Modelling, Data Analytics and AI in Engineering (MadeAI) Conference, Porto, Portugal.
Kazemi, P., Turrin, M., Andriotis, C.P., Entezami, A., Ghisi, A., Mariani, S., 2024. “Exploring structural sustainability of tall buildings subject to seismic loads”, Sustainable Structural Design Forum, Delft, The Netherlands.
Morato, P.G., Koniari, A.M., Khademi, S., Andriotis, C.P., 2024. “Building energy efficiency prediction and uncertainty quantification via Bayesian neural networks”, Georg Nemetschek Institute (GNI) Symposium & Expo on AI for the Built World, Munich, Germany.
Koniari, A.M., Morato, P.G., Andriotis, C.P., Khademi, S., Bianchi, S., Overend, M., 2024. “Building energy retrofit planning through Markov decision processes”, Georg Nemetschek Institute (GNI) Symposium & Expo on AI for the Built World, Munich, Germany.
Los, A., Moody, R., Andriotis, C.P., Khademi, S., Morato, P.G., 2024. “Developing energy communities with intelligent and sustainable technologies – first results”, European Geosciences Union (EGU) General Assembly, Vienna, Austria.
Andriotis C.P., Metwally, Z., 2023. “Inspection and maintenance planning through hierarchical resource allocation reinforcement learning”, Workshop on Predictive Maintenance: Let the Data Maintain the Model, Leiden, The Netherlands.
Bhustali, P., Andriotis, C.P., 2023. “Scalable inspection and maintenance planning for stochastically degrading engineering systems”, Workshop on Predictive Maintenance: Let the Data Maintain the Model, Leiden, The Netherlands.
Morato, P., Andriotis, C.P., Papakonstantinou, K.G., 2023. “From partial and limited structural health data to optimal management of engineering systems”, Engineering Mechanics Institute Conference (EMI), Atlanta, GA, USA.
Kazemi, P., Turrin, M., Andriotis, C.P., Entezami, A., Ghisi, A., Mariani, S., 2023. “Exploring architectural forms of tall buildings subject to seismic loads using deep learning surrogate models for structural sustainability”, Sustainable Structural Design Forum, Delft, The Netherlands.
Andriotis C.P., and Metwally, Z., 2022. “Optimizing resource allocation strategies for system-level inspection and maintenance planning”, 32nd European Conference on Safety and Reliability (ESREL), Dublin, Ireland.
Andriotis, C. P., and Papakonstantinou, K.G., 2022. “Stochastic optimization of risk-constrained management policies for deteriorating systems under state and model uncertainties”, Engineering Mechanics Institute Conference (EMI), Baltimore, MD, USA.
Morato, P.G., Andriotis, C.P., Papakonstantinou, K.G., and Rigo, P., 2022. “Model updating, condition assessment, and maintenance of multi-component systems under correlated deterioration processes”, Engineering Mechanics Institute Conference (EMI), Baltimore, MD, USA.
Saifullah, M., Andriotis, C.P., Papakonstantinou, K.G., and Stoffels, S.M., 2022. “Decentralized actor-critic deep reinforcement learning approach for optimal life-cycle management of transportation networks”, Engineering Mechanics Institute Conference (EMI), Baltimore, MD, USA.
Andriotis, C.P., and Papakonstantinou, K.G., 2022. “Deep reinforcement learning for stochastic optimal control of complex systems under constraints”, Society for Industrial and Applied Mathematics (SIAM) Conference on Uncertainty Quantification, Atlanta, GA, USA.
Altamimi, A.L., Lagoa, C., Borges, J., McDill, M., Andriotis, C.P., and Papakonstantinou, K.G., 2022. “Large-scale wildfire mitigation through deep reinforcement learning”, 19th Symposium on Systems Analysis in Forest Resources, Estes Park, CO, USA.
Andriotis C.P., and Papakonstantinou, K.G., 2021. “Deep reinforcement learning approach to structural inspection and maintenance policy optimization subject to life-cycle reliability constraints”, 14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control (EUROGEN), Athens, Greece, 2021.
Andriotis C.P., Papakonstantinou, K.G., and Chatzi, E.N., 2021. “Value of structural health information: Theoretical properties and connections to stochastic optimal control”, Engineering Mechanics Institute Conference (EMI), New York, NY.
Andriotis C.P., and Papakonstantinou, K.G., 2021. “Partially observable Markov decision processes solutions for life-cycle inspection and maintenance planning under short- and long-term budget constraints”, Engineering Mechanics Institute Conference (EMI), New York, NY.
Morato, P.G., Andriotis, C.P., Papakonstantinou, K.G., Hlaing, N., and Rigo, P., 2021. Optimal management of offshore wind structural systems via deep reinforcement learning and Bayesian networks”, Wind Energy Science Conference (WESC), Hannover, Germany.
Andriotis C.P., and Papakonstantinou, K.G., 2019. “Stochastic control in partially observable structural domains using deep actor-critic reinforcement learning”, Engineering Mechanics Institute Conference (EMI), Pasadena, CA, USA.
Andriotis C.P., and Papakonstantinou, K.G., and Chatzi, E.N., 2019. “Value of information assessment of structural health monitoring through optimal stochastic control”, Engineering Mechanics Institute Conference (EMI), Pasadena, CA, USA.
Andriotis C.P., and Papakonstantinou, K.G., 2018. “Deep reinforcement learning for optimal decision-making of large engineering systems”, Engineering Mechanics Institute Conference (EMI), Cambridge, MA, USA.
Andriotis C.P., and Papakonstantinou, K.G., 2018. “Learning hidden structural deterioration using recurrent neural networks”, Engineering Mechanics Institute Conference (EMI), Cambridge, MA, USA.
Lyritsakis, C., Andriotis C.P., and Papakonstantinou, K.G., 2018. “Hybrid beam element formulation based on exact kinematics and nonlinear programming”, Engineering Mechanics Institute Conference (EMI), Cambridge, MA, USA.
Papakonstantinou K.G., Andriotis C.P., 2017. “From monitored data to autonomous informed decisions”, Engineering Mechanics Institute Conference (EMI), San Diego, CA, USA.
Andriotis C.P., and Papakonstantinou, K.G., 2017. “Multi-featured generalized fragility functions from a statistical learning perspective”, Engineering Mechanics Institute Conference (EMI), San Diego, CA, USA.
Andriotis C.P., and Papakonstantinou, K.G., 2016. “Elastoplastic and geometrically nonlinear analysis of frame structures based on generalized total potential energy functional”, Engineering Mechanics Institute Conference (EMI), Vanderbilt, TN, USA.
Hooks, E.M., McNeil, S., Lattanzi, D., Papakonstantinou, K., Stoffels, S., Zhou, W., Kamranfar, P., Saifullah, M., Andriotis, C.P., and Withers, A., 2021. "Strategic Prioritization and Planning of Multi-Asset Transportation Infrastructure Maintenance, Rehabilitation, and Improvements: Phase 1–Prioritization through Optimization", No. CIAM-UTC-REG5, Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS).
Papakonstantinou, K.G., Guler, I., Gayah, V., Saifullah, M., Andriotis, C.P., and Lu, M., 2021. "AI-enabled Fiscally Constrained Lifecycle Asset Management for Infrastructure Systems", No. CIAM-UTC-REG21, LTI 2022-05, Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS).
Saifullah, M., Papakonstantinou, K. Andriotis, C.P, 2025. Apparatus and method for improved inspection and/or maintenance management”, U.S. Patent Application 18/853,426.
Multi-agent inspection & maintenance planning using reinforcement learning
Optimality of decentralization in multi-agent reinforcement learning
Jax implementation for transport network intervention planning with reinforcement learning
Active learning with Bayesian neural networks & foundation models for audit planning
Data for active learning with Bayesian neural networks & foundation models for buildings
Faculty of Architecture & Built Environment
Delft University of Technology
Julianalaan 134, 2628 BL, Delft
email: c [dot] andriotis [at] tudelft [dot] nl
Copyright @ C.P. Andriotis