Imperial College London - United Kingdom
AUTHOR PROFILE
GOOGLE SCHOLAR
SCOPUS
ORCID
SUMMARY
Theo Glashier is a motivated PhD student at Imperial College London specializing in infrastructure monitoring and structural health assessment. His research focuses on data-driven strategies for interpreting measurement data from civil infrastructure under varying environmental conditions. With a keen interest in applying statistical methods and machine learning, Theo aims to advance real-time performance evaluations of critical structures. His hands-on experience includes working with the MX3D 3D-printed steel bridge and mentoring Master’s students. He is actively involved in academic dissemination and conference participation, laying the foundation for a promising research career in civil infrastructure health monitoring.
EDUCATION
Theo is currently completing his PhD in Civil and Environmental Engineering at Imperial College London (2021–2024), with a thesis focused on temperature-based measurement interpretation in critical civil infrastructure. He holds a First-Class Honours MEng in Mechanical Engineering from the University of Sheffield (2015–2019). His academic path includes a strong foundation in solid mechanics, structural dynamics, and nonlinear system analysis. His undergraduate and postgraduate studies have consistently emphasized research-led innovation, reflected in high-impact projects and publications. He has developed specialized expertise in regression models, machine learning applications, and sensor-based structural monitoring techniques.
PROFESSIONAL EXPERIENCE
Theo’s experience spans academia and industry. He worked at Total Energies in France (2019–2020) managing large-scale sensor data from offshore assets, leading a CO₂ monitoring initiative, and building a data infrastructure in PI System. He also contributed to NASA’s High-Altitude Student Platform via Project Sunbyte, launching a balloon-mounted solar flare imaging system. His research career includes fieldwork on the MX3D Bridge in Amsterdam and multiple in-person large-scale structural tests. He has developed strong communication skills through presenting at global conferences and managing collaborative research efforts with both academic and industrial stakeholders.
RESEARCH INTEREST
Theo is passionate about structural health monitoring and real-time infrastructure assessment. His core research explores data preparation techniques to filter environmental and operational variability from structural measurements. He integrates statistical regression, machine learning, and high-performance computing to derive accurate and interpretable predictions from complex datasets. Current projects focus on temperature-based interpretations and long-term monitoring strategies for steel bridges. His work advances the application of smart sensors and computational modeling in civil engineering, aiming to enhance the resilience, safety, and longevity of critical infrastructure systems through automated diagnostics and predictive analytics.
AWARD AND HONOR
Theo has earned several academic honors, including the Skempton PhD Scholarship and 2nd Prize at the Imperial College PhD Summer Showcase 2023. He received research travel grants such as the Milija Pavlovic Fund and institutional support to attend leading conferences like EWSHM and IABMAS 2024. His presentation skills led to an invitation to speak at the 25th Young Researchers Conference. These accolades reflect his exceptional contributions to structural monitoring research, recognized by both academic peers and industry professionals. They also underscore his ability to communicate complex findings to diverse audiences.
RESEARCH SKILL
Theo has advanced technical proficiency in Python, Matlab, and C, alongside hands-on expertise in SolidWorks, Ansys, and PI System for data acquisition. He is well-versed in machine learning for regression analysis, statistical data filtering, and signal visualization. His practical experience includes designing and deploying sensor networks, conducting in-situ structural testing, and high-performance computing for large datasets. He is multilingual, fluent in English and French, and conversational in Italian and Spanish. His interdisciplinary skill set equips him to manage complex infrastructure datasets and lead data-centric engineering projects with both academic and commercial stakeholders.
PUBLICATIONS
Title: Temperature-based measurement interpretation of the MX3D Bridge
Authors: T. Glashier, R. Kromanis, C. Buchanan
Journal: Engineering Structures, Vol. 305, Article 116736, 2024
Title: An iterative regression-based thermal response prediction methodology for instrumented civil infrastructure
Authors: T. Glashier, R. Kromanis, C. Buchanan
Journal: Advanced Engineering Informatics, Vol. 60, Article 102347, 2024
Title: Temperature-based Damage Detection for the Commissioning Dataset of the MX3D Bridge
Authors: T. Glashier, R. Kromanis, C. Buchanan
Journal: 11th European Workshop on Structural Health Monitoring (EWSHM), 2024
Title: Thermal response prediction of the MX3D bridge's operational dataset
Authors: T. Glashier, C. Buchanan, R. Kromanis
Journal: Bridge Maintenance, Safety, Management, Digitalization and Sustainability, 2024
Title: Predicting the environmental response of critical infrastructure, using the first metal 3D printed structure as a case study
Author: T. Glashier
Journal: Proceedings of the 25th Young Researchers Conference, 2023
CONCLUSION
Theo Glashier exemplifies the new generation of civil engineers driving innovation in structural health monitoring. His blend of technical skill, academic dedication, and practical experience positions him as a rising contributor to resilient infrastructure systems. With a clear vision for a research-led career, he seeks to bridge the gap between data science and civil engineering. His work not only provides scientific insight but also addresses real-world challenges in maintaining and assessing the health of built environments. Theo’s research trajectory reflects excellence, innovation, and a strong commitment to societal infrastructure advancement.