Publications
Journals
- PG Morato, CP Andriotis, KG Papakonstantinou, P Rigo (2023). Inference and dynamic decision-making for deteriorating systems with probabilistic dependencies through Bayesian networks and deep reinforcement learning. Reliability Engineering & System Safety. [https://www.sciencedirect.com/science/article/pii/S0951832023000595]
- 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. [https://www.sciencedirect.com/science/article/pii/S0167473021000631]
- Chen, Z., Khademi, S., Ledoux, H. and Nan, L. (2022). Reconstructing Compact Building Models from Point Clouds Using Deep Implicit Fields. ISPRS Journal of Photogrammetry and Remote Sensing. [Reconstructing Compact Building Models from Point Clouds Using Deep Implicit Fields]
- Bier, H., Khademi, S., Van Engelenburg, C.J., Prendergast, J.M. and Peternel, L. (2022). Computer Vision and Human–Robot Collaboration Supported Design-to-Robotic-Assembly. Construction Robotics, Springer International Publishing. [https://link.springer.com/article/10.1007/s41693-022-00084-1]
- Andriotis, C.P.and Papakonstantinou, K.G. (2020). Deep reinforcement learning driven inspection and maintenance planning under incomplete information and constraints. Reliability Engineering & System Safety. [https://www.sciencedirect.com/science/article/pii/S095183202100106X]
- Andriotis, C.P.and Papakonstantinou, K.G. (2020). Value of structural health information in partially observable stochastic environments. Structural Safety. [https://www.sciencedirect.com/science/article/pii/S0167473020301508]
- Serajeh, R., Khademi, S., Mousavinia, A. and Van Gemert, J.C. (2020). On Sensitive Minima in Margin-Based Deep Distance Learning. IEEE Access. [(PDF) On Sensitive Minima in Margin-Based Deep Distance Learning (researchgate.net)]
Conferences
- CP Andriotis, Z Metwally (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. [www.tara.tcd.ie/bitstream/handle/2262/103609/submission_476.pdf?sequence=1]
- M Saifullah, CP Andriotis, KG Papakonstantinou (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. [www.tara.tcd.ie/bitstream/handle/2262/103618/submission_488.pdf?sequence=1&isAllowed=y]
- C Lathourakis, C Andriotis, A Cicirello (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. [www.tara.tcd.ie/bitstream/handle/2262/103339/submission_222.pdf?sequence=1]
- PG Morato, KG Papakonstantinou, CP Andriotis, N Hlaing, A Kolios (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. [www.tara.tcd.ie/bitstream/handle/2262/103225/submission_65.pdf?sequence=1]
- F Molaioni, Z Rinaldi, CP Andriotis (2023). Assessing life-cycle seismic fragility of corroding reinforced concrete bridges through dynamic Bayesian networks. 8th International Symposium on Life-Cycle Civil Engineering (IACCE), Milan, Italy. [https://www.taylorfrancis.com/chapters/oa-edit/10.1201/9781003323020-62/assessing-life-cycle-seismic-fragility-corroding-reinforced-concrete-bridges-dynamic-bayesian-networks-molaioni-rinaldi-andriotis]
- F Mostafavi, S Khademi (2023). Micro-Climate Building Context Visualization: A pipeline for generating buildings’ environmental context maps using numerical simulation data. 41st Conference on Education and Research in Computer Aided Architectural. [https://research.tudelft.nl/en/publications/micro-climate-building-context-visualization-a-pipeline-for-gener]
- 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. [par.nsf.gov/servlets/purl/10441107]
- Morato, P.G., Papakonstantinou, K.G.and Andriotis, C.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. [https://research.tudelft.nl/en/publications/managing-offshore-wind-turbines-through-markov-decision-processes]
- 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. [https://research.tudelft.nl/en/publications/appraisal-and-mathematical-properties-of-fragility-analysis-metho]
- 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. [par.nsf.gov/servlets/purl/10427029]
- 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. [https://www.frontiersin.org/articles/10.3389/ffgc.2022.734330/full#:~:text=In%20this%20work%2C%20we%20propose%20a%20Deep%20Reinforcement,wildfire%20risks%20by%20determining%20highly%20efficient%20management%20policies.]
- Yildiz, B., Khademi, S., Siebes, R.M. and Van Gemert, J. (2022). AmsterTime: A Visual Place Recognition Benchmark Dataset for Severe Domain Shift. 26th International Conference on Pattern Recognition (ICPR), Montreal Quebec. [[2203.16291] AmsterTime: A Visual Place Recognition Benchmark Dataset for Severe Domain Shift (arxiv.org)]
- Shi, X., Khademi, S., Li, Y. and Van Gemert, J. (2021). Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels. 25th International Conference on Pattern Recognition (ICPR), Milan, Italy. [[2010.08644] Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels (arxiv.org)]
- AM Koniari, C Andriotis, F Oikonomopoulou (2023). Minimum mass cast glass structures under performance and manufacturability constraints. International Conference on Computer-Aided Architectural Design Futures. [https://repository.tudelft.nl/islandora/object/uuid:f07b0d6f-820e-4c30-9401-27dbb8cc02f2]
Workshops
- J van Remmerden, M Kenter, D Roijers, Y Zhang, C Andriotis, Z Bukhsh (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 2023), Krakow, Poland. [https://modem2023.vub.ac.be/papers/MODeM2023_paper_15.pdf]
- Van Engelenburg, C.J., Khademi, S. and Van Gemert, J.C. (2023). SSIG: A Visually-Guided Graph Edit Distance for Floor Plan Similarity. Proceedings of the IEEE/CVF International Conference on Computer Vision. [https://openaccess.thecvf.com/content/ICCV2023W/CVAAD/html/van_Engelenburg_SSIG_A_Visually-Guided_Graph_Edit_Distance_for_Floor_Plan_Similarity_ICCVW_2023_paper.html]
- Hlaing Nandar, Pablo Gabriel Morato Dominguez, KG Papakonstantinou, CP Andriotis, Philippe Rigo (2022). Interpretation of offshore wind management policies identified via partially observable Markov decision processes. European Academy of Wind Energy PhD Seminar. [EAWE_PhD_Seminar_InterpretationPOMDPs_V2_Oct3.pdf (uliege.be)]
Others
- Mager, T., Khademi, S., Siebes, R., Van Gemert, J., De Boer, V., Löffler, B. and Hein, C. (2023). Computer Vision and Architectural History at Eye Level: Mixed Methods for Linking Research in the Humanities and in Information Technology. Mixing Methods: Practical Insights from the Humanities in the Digital Age. [https://research.rug.nl/en/publications/computer-vision-and-architectural-history-at-eye-level-mixed-meth]
- Khademi, S., Van Engelenburg, C.J., Van Gemert, J., Mostafavi, F., Armeni, I., Standfest, M. and Franzen, M. (2023). 1st Computer Vision Aided Architectural Design Workshop. International Conference on Computer Vision. [https://cvaad-workshop.github.io/]
- Khademi, S., Van Engelenburg, C.J., Mostafavi, F., Rout, A., Pohl, D., Balaban, O. and Law, S. (2023). Machine Learning Data for Architectural Design. CAAD futures. [https://www.caadfutures2023.nl/co-creation]
- Hooks, E.M., McNeil, S., Lattanzi, D., Papakonstantinou, K., Stoffels, S., Zhou, W., Kamranfar, P., Saifullah, M.andriotis, C. and Withers, A. (2021). Strategic Prioritization and Planning of Multi-Asset Transportation Infrastructure Maintenance, Rehabilitationand Improvements: Phase 1–Prioritization through Optimization. Repository & Open Science Acces Portal (Rosap). [https://rosap.ntl.bts.gov/view/dot/62725]
- 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. Repository & Open Science Acces Portal (Rosap). [https://rosap.ntl.bts.gov/view/dot/60831]
Journals
Applied AI
- 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.
- Andriotis, C.P., Papakonstantinou, K.G., and Chatzi, E.N., 2021. “Value of structural health information in partially observable stochastic environments”, Structural Safety, 92, 102072.
Fundamental AI
- R. Serajeh, S. Khademi, A. Mousavinia and J. C. Van Gemert, "On Sensitive Minima in Margin-Based Deep Distance Learning," in IEEE Access, vol. 8, pp. 145067-145076, 2020, doi: 10.1109/ACCESS.2020.3013560.
- Z Chen, S Khademi, H Ledoux, L Nan ”Reconstructing Compact Building Models from Point Clouds Using Deep Implicit Fields”. Submitted to ISPRS Journal of Photogrammetry and Remote Sensing. 2021.
Conference Abstracts & Proceedings
Applied AI
- Andriotis C.P., and Papakonstantinou, K.G., “Optimizing policies for deteriorating systems using intrinsic action structuring and value of information”, 13th International Conference on Structural Safety & Reliability (ICOSSAR), Shanghai, China, 2022.
- Morato, P.G., Papakonstantinou, K.G., and Andriotis, C.P., “Managing off-shore wind turbines through Markov decision processes and dynamic Bayesian networks”, 13th International Conference on Structural Safety & Reliability (ICOSSAR), Shanghai, China, 2022.
- Yi, S., Papakonstantinou, K.G., Andriotis, C.P., and Song, J., “Appraisal and mathematical properties of fragility analysis methods”, 13th International Conference on Structural Safety & Reliability (ICOSSAR), Shanghai, China, 2022.
- Saifullah, M., Andriotis C.P., Papakonstantinou, K.G., and Stoffels, S.M., “Deep reinforcement learning-based life-cycle management of deteriorating transportation systems”, 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS), Barcelona, Spain, 2022.
- Andriotis, C.P., and Papakonstantinou, K.G., “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, 2022.
- Andriotis, C. P., and Papakonstantinou, K.G., “Stochastic optimization of risk-constrained management policies for deteriorating systems under state and model uncertainties”, Engineering Mechanics Institute Conference (EMI), Baltimore, MD, USA, 2022.
- Morato, P.G., Andriotis, C.P., Papakonstantinou, K.G., and Rigo, P., “Model updating, condition assessment, and maintenance of multi-component systems under correlated deterioration processes”, Engineering Mechanics Institute Conference (EMI), Baltimore, MD, USA, 2022.
- Saifullah, M., Andriotis, C.P., Papakonstantinou, K.G., and Stoffels, S.M., “Decentralized actor-critic deep reinforcement learning approach for optimal life-cycle management of transportation networks”, Engineering Mechanics Institute Conference (EMI), Baltimore, MD, USA, 2022.
- Altamimi, A.L., Lagoa, C., Borges, J., McDill, M., Andriotis, C.P., and Papakonstantinou, K.G., “Large-scale wildfire mitigation through deep reinforcement learning”, 19th Symposium on Systems Analysis in Forest Resources, Estes Park, CO, USA, 2022.
- Andriotis C.P., and Papakonstantinou, K.G., “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.
- Morato, P.G., Andriotis, C.P., Papakonstantinou, K.G., Hlaing, N., and Rigo, P., “Optimal management of offshore wind structural systems via deep reinforcement learning and Bayesian networks”, Wind Energy Science Conference (WESC), Hannover, Germany, 2021.
- Andriotis C.P., Papakonstantinou, K.G., and Chatzi, E.N., “Value of structural health information: Theoretical properties and connections to stochastic optimal control”, Engineering Mechanics Institute Conference (EMI), New York, NY, USA, 2021.
- Andriotis C.P., and Papakonstantinou, K.G., “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, USA, 2021
Fundamental AI
- B Yildiz, S Khademi, RM Siebes, J van Gemert, “AmsterTime: A Visual Place Recognition Benchmark Dataset for Severe Domain Shift”, 26TH International Conference on Pattern Recognition (ICPR) 2022.
- X Shi, S Khademi, Y Li, J. van Gemert, “Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels". 25TH International Conference on Pattern Recognition (ICPR) 2021.
Technical Reports
Applied AI
- Hooks, E.M., McNeil, S., Lattanzi, D., Papakonstantinou, K., Stoffels, S., Zhou, W., Kamranfar, P., Saifullah, M., Andriotis, C. 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).
- 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)(UTC).