Apostolos Parasyris | Earth | Best Scholar Award

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Mr. Apostolos Parasyris | Earth | Best Scholar Award

Mr. Apostolos Parasyris, University of Strathclyde, United Kingdom

Apostolos Parasyris is a multidisciplinary researcher and engineer specializing in machine learning applications for structural health monitoring, climate impact assessment, and geotechnical engineering. He is a doctoral candidate in Machine Learning at the University of Strathclyde and currently serves as a Research Scientist and Project Manager at Risa Sicherheitsanalysen GmbH in Berlin. With extensive experience in EU research projects and hands-on technical design, he integrates AI-driven models and data science methodologies to enhance infrastructure resilience, sustainability, and safety across various sectors.

PROFILE

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Educational Details

Apostolos Parasyris holds multiple advanced degrees that span a range of engineering disciplines. He earned a Master of Engineering (M.Eng.) in Geotechnical Engineering, followed by two 2-year Master’s degrees—one in Energy (Chemical Engineering) and another in Structural Engineering (Civil Engineering). Currently, he is in the fifth year of his Doctoral studies in Machine Learning, specializing in Electronics and Electrical Engineering at the University of Strathclyde.

Professional Experience

Apostolos has a diverse and extensive professional background, with experience in both research and applied technical projects. As a Structural Designer, he has contributed to high-profile infrastructure projects, including the Kastelli Airport design, Athens Metro Line 4, “Karellas” Bridge widening, and the pedestrian “Hellinikon” Bridge. Currently, Apostolos is a Machine Learning Research Scientist and Project Manager at Risa Sicherheitsanalysen GmbH in Berlin, Germany, where he focuses on applying AI and machine learning to innovative projects such as the Horizon EU projects Preserve (AI models for cybercrime detection), Armadillo (AI-driven portable GHB detection tools for crime prevention), and RiskAdapt (asset-level risk modeling to manage climate-induced extreme events).

In addition to his professional role, Apostolos has also participated in several EU and UK research projects related to infrastructure resilience and structural inspection. Notably, these include RESIST (extreme event resilience in transportation), AEROBI (aerial robotic systems for bridge inspection), RECONASS (construction damage assessment and recovery planning), and ROBINSPECT (robotic inspection for tunnels). He has gained recognition as a researcher, achieving six citations and an h-index of nine. He is an active member of prestigious professional organizations, including the IEEE (Institute of Electrical and Electronics Engineers), GRSS (Geoscience and Remote Sensing Society), and TEE (Technical Chamber of Greece).

Research Interests

Apostolos’s research interests are broad yet cohesive, covering geophysics, geotechnical engineering, and subsurface exploration. His work in structural dynamics, structural health monitoring, and machine learning intersects with his focus on landslide prediction and climate impact analysis. Apostolos is currently involved in projects developing AI-based tools for asset risk assessment under climate-induced extreme events and tools for early detection of slope instabilities linked to landslides and debris flows.

Top Notable Publications

Article
Parasyris, A., Stankovic, L., & Stankovic, V. (2024). A machine learning-driven approach to uncover the influencing factors resulting in soil mass displacement. Geosciences (Switzerland), 14(8), 220.
(Citations: 0)

Conference Paper
Parasyris, A., Stankovic, L., & Stankovic, V. (2024). Dimensionality reduction for visualization of hydrogeophysical and meteorological recordings on a landslide zone. International Geoscience and Remote Sensing Symposium (IGARSS), pp. 1864–1868.
(Citations: 1)

Article
Parasyris, A., Stankovic, L., & Stankovic, V. (2023). Synthetic data generation for deep learning-based inversion for velocity model building. Remote Sensing, 15(11), 2901.
(Citations: 4)

Conference Paper
Parasyris, A., Stankovic, L., Pytharouli, S., & Stankovic, V. (2023). Near surface full waveform inversion via deep learning for subsurface imaging. Expanding Underground – Knowledge and Passion to Make a Positive Impact on the World: Proceedings of the ITA-AITES World Tunnel Congress (WTC 2023), pp. 2829–2836.
(Citations: 1)

Conference Paper
Parasyris, A., & Bairaktaris, D. (2023). Innovative methodology for advanced structural condition assessment of tunnels. Expanding Underground – Knowledge and Passion to Make a Positive Impact on the World: Proceedings of the ITA-AITES World Tunnel Congress (WTC 2023), pp. 2493–2500.
(Citations: 1)

Conclusion

Given his strong academic foundation, interdisciplinary research experience, and contributions to impactful projects, Mr. Apostolos Parasyris presents a compelling case for the Research for Best Scholar Award. His work aligns with the award’s objectives, showcasing innovative approaches to solving complex engineering challenges, particularly in the areas of machine learning applications, structural resilience, and natural disaster prevention. This forward-looking perspective and dedication make him a promising candidate deserving of recognition in his field.