Fariba Shokoohi | Engineering and Technology | Best Researcher Award

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Dr. Fariba Shokoohi | Engineering and Technology | Best Researcher Award

SR.C., Islamic Azad University | Iran

Dr.  Fariba Shokohi is a civil engineering researcher specializing in construction engineering and management. She is currently pursuing her Ph.D. in Civil Engineering at the Islamic Azad University, focusing on lean construction, sustainability analytics, and multi-criteria decision-making. Her academic path includes dual master’s degrees in Construction Engineering & Management and Industrial Engineering, supported by a strong foundation in civil engineering and cartography. Professionally, she has served in senior technical, design, supervision, and project management roles across major national organizations, including construction engineering firms, banking infrastructure companies, and intelligent systems corporations. Her expertise spans project management, sustainability assessment, BIM applications, fuzzy MCDM techniques, quality evaluation models, and advanced engineering software. She has authored impactful publications on lean–sustainable construction integration, fuzzy DEMATEL, green building systems, and self-healing concrete. Her research interests include sustainable construction, lean project delivery, green roofs, carbon emission reduction, intelligent project systems, and integrated management frameworks. She has actively contributed to national conferences and international journals and is a senior member of professional engineering societies. Dr. Shokohi continues to advance innovative methods in sustainable project management and construction optimization.

Profile : Orcid

Featured Publications

Shokoohi, F. (2025). Multi-dimensional sensitivity analysis of lean and sustainable construction: A novel MTDA approach for integrated project management. International Journal of Construction Management. (Accepted, June 2025)

Shokoohi, F. (2023). Application of focus group method in extended fuzzy DEMATEL technique: Integrating effective factors in lean and sustainable construction. Andisheye Amari Journal, 27(2), 105–120.

Rabieifar, H., Shokoohi, F., & Ashtiani, Z. (2021). Application of bacteria in concrete repair and its effect on self-healing properties: A review study. In 23rd National Concrete and Earthquake Conference, Concrete Research Center (METEB).

Farrokhzadeh, F., & Shokoohi, F. (2020). Integration of lean thinking and sustainable development in HSE management of the construction industry. Journal of Defense Maintenance Engineering Research, 3(2), 58–74.

Shokoohi, F., & Ravanshadnia, M. (2023). Evaluation of green roofs in reducing carbon emissions and improving environmental sustainability: A case study of a building in Tehran using DesignBuilder software. In 8th International Conference on Civil Engineering, Architecture, and Sustainable Green Urban Development.

Alexey Beskopylny | Civil Engineering | Best Researcher Award

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Prof. Dr. Alexey Beskopylny | Civil Engineering | Best Researcher Award

Don State Technical University | Russia

Dr. Alexey N. Beskopylny is a distinguished researcher and Vice Rector at Don State Technical University, serving as a Professor in the Department of Transport Systems. He holds a Doctor of Technical Sciences degree and has made significant contributions to civil and structural engineering, materials science, and transport systems. His studies span concrete technology, geopolymers, recycled construction materials, digital modeling, and structural optimization using AI and machine learning. Dr. Beskopylny’s works are frequently featured in high-impact journals such as Scientific Reports, Polymers, Buildings, and Applied Sciences. He has collaborated extensively on international projects focusing on sustainable materials and innovative construction technologies. Recognized for his academic excellence and leadership, he has received multiple institutional honors for advancing the field of transport infrastructure and sustainable construction. His continued efforts contribute to the modernization of engineering education and the promotion of environmentally responsible building practices worldwide.

Profile : Orcid

Featured Publications

Zubarev, K. P., Razveeva, I., Beskopylny, A. N., Stel’makh, S. A., Shcherban’, E. M., Mailyan, L. R., Shakhalieva, D. M., Chernil’nik, A., & Nikora, N. I. (2025). Predicting the strength of heavy concrete exposed to aggressive environmental influences by machine learning methods. Buildings, 15(21), Article 3998.

Özkılıç, Y. O., Kalkan, İ., Aksoylu, C., Madenci, E., Umiye, O. A., Althaqafi, E., Stel’makh, S. A., Shcherban’, E. M., & Beskopylny, A. N. (2025). Effect of stirrup spacing and recycled steel wires on the shear and energy dissipation of pultruded GFRP hybrid beams. Journal of Engineered Fibers and Fabrics, 20, Article 15589250251380680.

Ecemiş, A. S., Yildizel, S. A., Beskopylny, A. N., Stel’makh, S. A., Shcherban’, E. M., Aksoylu, C., Madenci, E., & Özkılıç, Y. O. (2025). Sustainable concrete with waste tire rubber and recycled steel fibers: Experimental insights and hybrid PINN–CatBoost prediction. Polymers, 17(21), Article 2910.

Özkılıç, Y. O., Başaran, B., Aksoylu, C., Karalar, M., Zeybek, Ö., Althaqafi, E., Beskopylny, A. N., Stel’makh, S. A., Shcherban’, E. M., & Umiye, O. A. (2025). Bending performance of reinforced concrete beams with partial waste glass aggregate replacement assessed by experimental, theoretical and digital image correlation analyses. Scientific Reports, 15, Article 20716.

Stel’makh, S. A., Shcherban’, E. M., Beskopylny, A. N., Mailyan, L. R., Shilov, A. A., Razveeva, I., Oganesyan, S., Pogrebnyak, A., Chernil’nik, A., & Elshaeva, D. (2025). Enhancing the mechanical properties of sulfur-modified fly ash/metakaolin geopolymers with polypropylene fibers. Polymers, 17(15), Article 2119.

Marius Šumanas | Computer Vision | Best Researcher Award

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Assist. Prof. Dr Marius Šumanas | Computer Vision | Best Researcher Award

Vilnius Tech | Lithuania

Dr. Marius Šumanas is an Associate Professor in the Department of Mechatronics, Robotics, and Digital Manufacturing at Vilnius Gediminas Technical University (VILNIUS TECH).  His research interests encompass robotics, machine learning, and digital manufacturing. Dr. Šumanas has authored several publications, including a study on improving positioning accuracy of articulated robots using deep Q-learning algorithms. He has also participated in various conferences, presenting topics related to machine learning applications in robotics. In addition to his academic roles, Dr. Šumanas has practical experience in the industry. Since 2018, he has been working as a Process Engineer and ERP Systems Business Analyst at MB Pramones algoritmas. He has also held positions in marketing and sales management in previous years. Dr. Šumanas’ work bridges the gap between theoretical research and practical application, contributing to advancements in robotics and digital manufacturing.

Profile : Orcid

Featured Publications

Andrijauskas, I., Šumanas, M., Dzedzickis, A., Tanaś, W., & Bučinskas, V. (2025). Computer vision-based optical odometry sensors: A comparative study of classical tracking methods for non-contact surface measurement. Sensors.

Šumanas, M., Treciokaite, V., Čerškus, A., Dzedzickis, A., Bučinskas, V., & Morkvenaite-Vilkonciene, I. (2022). Sitting posture monitoring using Velostat based pressure sensors matrix. In Smart Sensor Systems (pp. 1–12). Springer.

Bučinskas, V., Dzedzickis, A., Šumanas, M., Sutinys, E., Petkevicius, S., Butkiene, J., Virzonis, D., & Morkvenaite-Vilkonciene, I. (2022). Improving industrial robot positioning accuracy to the microscale using machine learning method. Machines, 10(10), 940.

Šumanas, M., Urbonis, D., Petronis, A., Stankaitis, S., Januškevičius, T., Iljin, I., & Dzedzickis, A. (2021). Evaluation of motion characteristics using absolute sensors. In Advances in Mechatronics and Intelligent Robotics (pp. 1–12). Springer.

Šumanas, M., Petronis, A., Urbonis, D., Januskevicius, T., Rasimavicius, T., Morkvenaite-Vilkonciene, I., Dzedzickis, A., & Bučinskas, V. (2021, April 22). Determination of excavator tool position using absolute sensors. In 2021 Open Conference of Electrical, Electronic and Information Sciences (eStream). IEEE.