Antonios Kamariotis

Antonios Kamariotis, M.Sc. (Hons)

Room: N3632

Phone: +49 89 289 23053

E-Mail: antonis.kamariotis@tum.de

Office hours: by arrangement

Since June 2023 | Scientific Assistant at the Structural Mechanics and Monitoring Group, ETH Zürich
2021 (Sept-Oct) | Visiting researcher at the Structural Mechanics and Monitoring Group, ETH Zürich
May 2019 - April 2023 | Ph.D. Student at the Engineering Risk Analysis Group, Technische Universität München, jointly with the Structural Mechanics and Monitoring Group, ETH Zürich.
2017 - 2019 | Student of the Bavarian Graduate School of Computational Engineering (BGCE)
2016 - 2019 | M.Sc. (Hons) in Computational Mechanics, Technische Universität München.
2010 - 2016 | Diploma in Civil Engineering, Aristotle University of Thessaloniki.

WS22/23: Teaching assistant for the lecture "Structural Reliability", TUM.
SS22: Teaching assistant for a new lecture "Prognostics and Health Management", TUM.
WS21/22: Teaching assistant for the lecture "Structural Reliability", TUM.
SS21: Co-organizer for the lecture series "Optimal decision making with structural health monitoring", TUM.
WS20/21: Teaching assistant for the lecture "Structural Reliability", TUM.
WS19/20: Teaching assistant for the lecture "Structural Reliability", TUM.
SS19: Teaching assistant for the lecture “Risk Assessment”, TUM.

Master thesis: Luca Sardi (2020-2021): Bayesian filtering for sequential estimation of structural deterioration.
Master thesis: Wanchang Zhang (2020): Estimating filtering distributions via a cross entropy based importance sampling scheme.
Honors Project: Wanchang Zhang (2020): Modal-based damage localization on a bridge-type monitored structure.

Antonios Kamariotis, Konstantinos Tatsis, Eleni Chatzi, Kai Goebel, Daniel Straub (2024). A metric for assessing and optimizing data-driven prognostic algorithms for predictive maintenance. Reliability Engineering & System Safety 242, 109723. https://doi.org/10.1016/j.ress.2023.109723
Antonios Kamariotis, Luca Sardi, Iason Papaioannou, Eleni Chatzi, Daniel Straub (2023), On off-line and on-line Bayesian filtering for uncertainty quantification of structural deterioration. Data-Centric Engineering 4, e17. https://doi.org/10.1017/dce.2023.13.
Antonios Kamariotis, Eleni Chatzi, Daniel Straub (2023), A framework for quantifying the value of vibration-based structural health monitoring, Mechanical Systems and Signal Processing 184, 109708, https://doi.org/10.1016/j.ymssp.2022.109708
Antonios Kamariotis, Eleni Chatzi, Daniel Straub (2022), Value of information from vibration-based structural health monitoring extracted via Bayesian model updating, Mechanical Systems and Signal Processing 166,108465, https://doi.org/10.1016/j.ymssp.2021.108465

Kamariotis A., Chatzi E., Straub D. (2022). Quantifying the value of vibration-based structural health monitoring considering environmental variability. In: Proceedings of the 13th International Workshop on Structural Health Monitoring, Stanford University, CA, USA.
Kamariotis A., Chatzi E., Straub D. (2022). The effect of the likelihood function on the value of SHM extracted via sequential Bayesian updating. In: Proceedings of ICOSSAR 2021-2022, 13th International Conference on
Structural Safety & Reliability, Tongji University, Shanghai, China.
Kamariotis A., Sardi L., Papaioannou I., Chatzi E., Straub D. (2022). A comparative assessment of online and offline Bayesian estimation of deterioration model parameters. In: Proceedings of IMAC XL, Orlando, Florida, USA.
Kamariotis A., Chatzi E., Straub D. (2021). Value of Information from SHM via estimating deterioration jump processes with particle filtering. In: Engineering Mechanics Institute Conference and Probabilistic Mechanics & Reliability Conference (EMI/PMC 2021). Virtual event.
Kamariotis, A., Straub, D., Chatzi, E. (2020). Optimal maintenance decisions supported by SHM: A benchmark study. In: Seventh International Symposium on Life-Cycle Civil Engineering 2020, Shanghai, China.
Kamariotis, A., Antinori, G., Papaioannou, I., Duddeck, F. (2019). Mixed aleatory-epistemic uncertainty quantification and sensitivity analysis. 17th International Probabilistic Workshop (IPW2019), Edinburgh, Scotland.

The effect of the likelihood function on the value of SHM extracted via sequential Bayesian updating. In: 13th International Conference on Structural Safety & Reliability, Tongji University, Shanghai, China (online).
Quantifying the value of vibration-based structural health monitoring considering environmental variability. In: European Workshop on Structural Health Monitoring (EWSHM 2022), Palermo, Italy.
Demonstrating the value of vibration-based structural health monitoring across different time scales. In: Engineering Mechanics Institute Conference (EMI 2022), Baltimore, Maryland, USA.
A comparative assessment of online and offline Bayesian estimation of deterioration model parameters. In: IMAC XL 2022, Orlando, Florida, USA.
Value of Information from SHM via estimating deterioration jump processes with particle filtering. In: Engineering Mechanics Institute Conference and Probabilistic Mechanics & Reliability Conference (EMI/PMC 2021). Virtual event.
Optimal maintenance decisions supported by SHM: A benchmark study. In: Seventh International Symposium on Life-Cycle Civil Engineering 2020, Online conference.
Mixed aleatory-epistemic uncertainty quantification and sensitivity analysis. In: 17th International Probabilistic Workshop (IPW2019), Edinburgh, Scotland.
Calibration of fatigue life models based on Bayesian methods. In: 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP), Crete, Greece, June 24-26.