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

 

Workshops

 

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).