Nevbahar Ekin | Applied Geophysics | Best Researcher Award

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Ms. Nevbahar Ekin | Applied Geophysics | Best Researcher Award

Assoc. Prof. Nevbahar Ekin at Suleyman Demirel University, Turkey

Assoc. Prof. Nevbahar EKİN 🎓 is a dedicated geophysicist at Süleyman Demirel University 🇹🇷, specializing in Applied Geophysics and Electrical/Electromagnetic methods. With strong academic foundations from Ankara University and ongoing doctoral work at SDU 🏫, her research focuses on subsurface characterization, particularly the geophysical evaluation of concrete and geological structures. She actively contributes to scientific journals and projects backed by TÜBİTAK 📘🔬. Fluent in intermediate English 🌐, she enhances her professional skills through specialized courses in education management. Her commitment to advancing engineering technology through geophysical innovation makes her a respected figure in her field 🛰️💡.

Professional Profile:

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📚 Education and Experience 

  • 🎓 Doctorate in Geophysical Engineering – Süleyman Demirel University (Ongoing)

  • 🎓 Postgraduate in Geophysical Engineering – Ankara University (Ongoing)

  • 🎓 Undergraduate in Geophysical Engineering – Ankara University

  • 💼 Associate Professor – Süleyman Demirel University, Faculty of Engineering and Natural Sciences

💼 Professional Development 

Assoc. Prof. Nevbahar EKİN is continually enhancing her professional and academic growth 📈. She completed specialized training in Education Management and Planning and received language education at Hacettepe University in 2012 🏫🗣️. With a B1 level in English proficiency 🌍, she is actively involved in national and international research collaboration, leveraging her skills in geophysics for infrastructure assessment and geological mapping 🧲📊. Her practical knowledge is supported by courses that refine both her technical and pedagogical approach, making her a well-rounded academic with a clear vision for educational leadership and scientific impact 🎯📘.

🔬 Research Focus 

Assoc. Prof. Nevbahar EKİN’s research falls within Engineering and Technology, specifically Geophysical Engineering 🛠️🌍. She focuses on Applied Geophysics, using electromagnetic and electrical methods to analyze underground structures, concrete integrity, and geological formations 🔎🧲. Her work contributes to safer construction, infrastructure planning, and natural resource evaluation, bridging theoretical knowledge with real-world applications 🏗️📡. Through field surveys and data analysis, she aims to improve geophysical modeling and diagnostic accuracy. Her research is critical in understanding subsurface behavior, especially in civil engineering contexts, environmental monitoring, and natural hazard assessment 🌐⚡.

🏅 Awards and Honors 

  • 🏆 Publication Incentive Award (TÜBİTAK) – Determination of Reinforced Concrete Strength by Electrical Resistivity, Journal of Applied Geophysics (October 2018)

  • 🏆 Publication Incentive Award (TÜBİTAK) – Prediction of Reinforced Concrete Strength by Ultrasonic Velocities, Journal of Applied Geophysics (September 2017)

Publication Top Notes

  1. The Relationships Between Ultrasonic P and S Wave Velocities and Resistivity in Reinforced Concrete

    • Journal: Construction and Building Materials

    • Date: June 2025

    • DOI: 10.1016/j.conbuildmat.2025.141475

    • Summary: This article likely investigates the correlation between the ultrasonic P-wave and S-wave velocities and the resistivity of reinforced concrete. These parameters are typically used for non-destructive testing to assess the structural integrity of concrete, which can help in determining its strength and durability.

  2. BETON DAYANIMI TAHMİNİNDE İKİLİ VE ÇOKLU DOĞRUSAL REGRESYON ANALİZLERİNİN KARŞILAŞTIRILMASI

    • Journal: Mühendislik Bilimleri ve Tasarım Dergisi

    • Date: March 20, 2025

    • DOI: 10.21923/jesd.1572342

    • Summary: This paper compares the use of bivariate and multivariate linear regression models in predicting the durability of concrete. Durability is a crucial aspect of concrete’s long-term performance, and the analysis can help in optimizing concrete mixes and understanding their behavior under various environmental conditions.

  3. Düşük Dayanımlı Donatılı Betonlarda Donatının Sismik Hızlara Etkisi

    • Journal: Türk Deprem Araştırma Dergisi

    • Date: June 24, 2023

    • DOI: 10.46464/tdad.1269738

    • Summary: This article focuses on the effect of reinforcement on seismic velocities in low-strength reinforced concrete. It is relevant for earthquake-resistant design, as understanding the influence of reinforcement on seismic wave propagation can help improve the resilience of structures in seismic zones.

  4. Betonların Elastik Modül Hesabında Poisson Oranının Önemi

    • Journal: Journal of Advanced Research in Natural and Applied Sciences

    • Date: December 29, 2020

    • DOI: 10.28979/jarnas.845156

    • Summary: This paper discusses the importance of Poisson’s ratio in the calculation of the elastic modulus of concrete. Elastic modulus is a key property of concrete, affecting its stiffness and how it deforms under stress. Poisson’s ratio, which relates lateral strain to axial strain, is critical in these calculations.

  5. Comparison of Static and Dynamic Elastic Moduli in Concrete: Effects of Compressive Strength, Curing Conditions, and Reinforcement

    • Journal: Iranian Journal of Science and Technology – Transactions of Civil Engineering

    • Date: 2020

    • DOI: 10.1007/s40996-020-00513-7

    • Summary: This study compares static and dynamic elastic moduli in concrete, analyzing how compressive strength, curing conditions, and reinforcement affect these properties. Static and dynamic moduli offer insights into concrete’s behavior under different loading conditions.

  6. Prediction of Mechanical and Physical Properties of Some Sedimentary Rocks from Ultrasonic Velocities

    • Journal: Bulletin of Engineering Geology and the Environment

    • Date: 2019

    • DOI: 10.1007/s10064-019-01501-6

    • Summary: This article applies ultrasonic velocity measurements to predict the mechanical and physical properties of sedimentary rocks, offering parallels to similar approaches in concrete testing, where ultrasonic testing is used to assess material properties.

  7. Determination of the Reinforced Concrete Strength by Apparent Resistivity Depending on the Curing Conditions

    • Journal: Journal of Applied Geophysics

    • Date: 2018

    • DOI: 10.1016/j.jappgeo.2018.03.007

    • Summary: This study examines how apparent resistivity can be used to determine the strength of reinforced concrete, focusing on how curing conditions impact this relationship. Resistivity measurements are useful for evaluating the condition of concrete, especially in harsh environments.

  8. Prediction of Reinforced Concrete Strength by Ultrasonic Velocities

    • Journal: Journal of Applied Geophysics

    • Date: 2017

    • DOI: 10.1016/j.jappgeo.2017.04.005

    • Summary: This paper explores the use of ultrasonic velocities to predict the strength of reinforced concrete. Ultrasonic pulse velocity testing is a non-destructive method that can offer valuable insights into concrete’s internal structure and strength without the need for physical sampling.

Conclusion

Assoc. Prof. Nevbahar EKİN is a highly suitable candidate for a Best Researcher Award. Her work is innovative, interdisciplinary, and nationally recognized. By applying geophysical techniques to solve practical engineering problems, she exemplifies impactful research that transcends traditional disciplinary boundaries.

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.