Curriculum Vitae

• 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.

Teaching

• 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.

Supervised theses/projects

• 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.

Journal Publications

• 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

Conference Publications

• 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.

Talks

• 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.