Konstantinos Azis | Engineering | Research Excellence Award

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Dr. Konstantinos Azis | Engineering | Research Excellence Award

Democritus University of Thrace | Greece

Dr. Konstantinos Azis is an accomplished environmental engineer and postdoctoral researcher whose work focuses on advanced wastewater treatment technologies, membrane bioreactor systems, and intelligent process control for sustainable water management. His research integrates biological, physicochemical, and automated monitoring approaches to optimize the performance of aerobic, anoxic, and anaerobic treatment processes, particularly in membrane systems and intermittently aerated bioreactors. He specializes in the design and operation of high-efficiency treatment units, development of real-time control strategies using programmable logic controllers, simulation-driven optimization with STOAT, and monitoring of key environmental parameters through continuous online sensors. His contributions extend to biological degradation studies of micropollutants, pharmaceuticals, and agrochemical contaminants, as well as post-treatment polishing processes such as activated carbon adsorption, sand filtration, ultrafiltration, and advanced oxidation. His research output demonstrates strong international visibility, with publications addressing membrane fouling mitigation, nutrient removal enhancement, biofouling dynamics, and energy-efficient aeration strategies. Dr. Azis has contributed significantly to environmental biotechnology by combining laboratory experimentation, field-scale evaluation, and computational modeling, offering practical solutions for water reuse and circular economy applications. His work has earned recognition through contributions to high-impact journals, service as a reviewer for numerous international scientific journals, and involvement as a Guest Editor in thematic issues focusing on sustainable wastewater treatment technologies. His scholarly influence is reflected in Scopus metrics: 118 citations and h-index 7, and Google Scholar metrics: 163 citations, h-index 8, i10-index 8, demonstrating the growing impact and relevance of his research across the wastewater engineering and environmental science communities. His scientific record and active research engagement position him as a strong candidate for the Research Excellence Award.

Publication Profile

Scopus | Orcid | Google Scholar

Featured Publications

Azis, K., Mavriou, Z., Karpouzas, D. G., Ntougias, S., & Melidis, P. (2021). Evaluation of sand filtration and activated carbon adsorption for the post-treatment of a secondary biologically-treated fungicide-containing wastewater. Processes, 9(7), 1223.

Azis, K., Zerva, I., Melidis, P., Caceres, C., Bourtzis, K., & Ntougias, S. (2019). Biochemical and nutritional characterization of the medfly gut symbiont Enterobacter sp. AA26 for its use as probiotics in sterile insect technique applications. BMC Biotechnology, 19(Suppl 2), 90.

Azis, K., Ntougias, S., & Melidis, P. (2021). NH4+-N versus pH and ORP versus NO3−-N sensors during online monitoring of an intermittently aerated and fed membrane bioreactor. Environmental Science and Pollution Research, 28(26), 33837–33843.

Azis, K., Ntougias, S., & Melidis, P. (2019). Fouling control, using various cleaning methods, applied on an MBR system through continuous TMP monitoring. Desalination and Water Treatment, 167, 343–350.

Papazlatani, C. V., Kolovou, M., Gkounou, E. E., Azis, K., Mavriou, Z., & others. (2022). Isolation, characterization and industrial application of a Cladosporium herbarum fungal strain able to degrade the fungicide imazalil. Environmental Pollution, 301, 119030.

Vasso Papadimitriou | Engineering | Best Researcher Award

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Ms. Vasso Papadimitriou | Engineering | Best Researcher Award

Aristotle University of Thessaloniki | Greece

Ms. Vasso Papadimitriou is an accomplished researcher and academic affiliated with the Aristotle University of Thessaloniki and the Region of Central Macedonia, Greece. Her research primarily focuses on construction project management, cost estimation models, and the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques, particularly Artificial Neural Networks (ANNs), in the field of building renovation and project planning. She has contributed significantly to the development of predictive and hybrid models that enhance accuracy in early-stage and final cost estimation for construction and renovation projects. Dr. Papadimitriou’s innovative work combines ANN methodologies, including Radial Basis Function (RBF) and Multilayer Perceptron (MLP) networks, with Multi-Criteria Decision-Making (MCDM) approaches such as the TOPSIS Methodology to create efficient, data-driven tools for project assessment and optimization. Her research also aligns with Sustainable Development Goals (SDG 9 and SDG 17), focusing on promoting innovation, infrastructure, and partnerships for sustainable growth. She has published in international peer-reviewed journals indexed in Scopus, Web of Science (SCI-Expanded, ESCI), and other scientific databases. According to Scopus, she has 6 publications, 3 citations, and an h-index of 1. On Google Scholar, she holds 14 total citations, an h-index of 3, and an i10-index of 1, while ResearchGate records 6 publications, 11 citations, and an h-index of 2. Her interdisciplinary approach bridges civil engineering, computer science, and digital construction, contributing to advancements in cost modeling and sustainable infrastructure management. Through her publications and research collaborations, Dr. Papadimitriou continues to make impactful contributions to the field of engineering innovation and AI-driven construction technology. Her outstanding achievements and innovative contributions to predictive modeling and sustainable construction management make her a deserving nominee for the Best Researcher Award.

Publication Profile

Scopus | Google Scholar

Featured Publications

Papadimitriou, V. E., & Aretoulis, G. N. (2024). A final cost estimating model for building renovation projects. Buildings, 14(4), 1072.

Papadimitriou, V. E., Aretoulis, G. N., & Papathanasiou, J. (2024). Radial Basis Function (RBF) and Multilayer Perceptron (MLP) comparative analysis on building renovation cost estimation: The case of Greece. Algorithms, 17(9), 390.

Papadimitriou, V., & Aretoulis, G. (2023). Neural network models as a cost prediction tool to prevent building construction projects from a failure—A literature review. Proceedings of the Erasmus+ PROSPER Project International Scientific Conference, 1–10.

Papadimitriou, V. E., & Aretoulis, G. N. (2025). An innovative approach regarding efficient and expedited early building renovation cost estimation utilizing ANNs and the TOPSIS methodology. Algorithms, 18(11), 696.

Kritikos, P., Papadimitriou, V., & Aretoulis, G. N. (2021). Required project designers’ attributes as perceived by male and female engineers. International Journal of Decision Support System Technology (IJDSST), 13(4), 1–15.

 

 

Qiusong Liang | Engineering | Best Researcher Award

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Ms. Qiusong Liang | Engineering | Best Researcher Award

Northeast Forestry University | China

Ms. Qiusong Liang is a promising mechanical engineering researcher whose work focuses on advanced simulation, optimization, and design of electro-hydraulic and electromechanical systems. Her research emphasizes multi-objective optimization, structural dynamics, and fluid–structure interaction analysis to enhance the performance and reliability of servo and direct-drive valve mechanisms. She skillfully integrates computational tools such as ANSYS, SolidWorks, Maxwell, and AMESim for high-precision modeling and simulation, contributing significantly to innovations in flow control mechanisms, torque motor optimization, and cavitation noise reduction in hydraulic systems. Her recent studies explore the dynamic characteristics of torque motors and the coupling effects between electromagnetic and fluid systems, leading to improved high-response servo valve technologies for industrial and military applications. Ms. Liang’s research excellence and innovative approach have been recognized through publications in internationally indexed journals and notable contributions to engineering design projects. She maintains an active research profile with Scopus- and Google Scholar–indexed publications, accumulating documented citations and a growing h-index that reflect her rising academic influence in the field of mechanical system optimization and applied simulation engineering. Her commitment to applied research, precision design, and interdisciplinary collaboration has earned her recognition as a recipient of the Best Researcher Award, highlighting her as one of the emerging leaders in smart mechanical systems and sustainable automation technologies.

Publication Profile

Orcid

Featured Publications

  • Zhang, J., Liang, Q., Sun, J., Yan, B., Hu, Z., & Sun, W. (2025, October 29). Multi-objective optimization of torque motor structural parameters in direct-drive valves based on genetic algorithm. Actuators, 14(11), 527.

Amr Ashmawi | Engineering | Best Researcher Award

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Mr. Amr Ashmawi | Engineering | Best Researcher Award

South Dakota State University | United States

Mr. Amr Ashmawi is a structural civil engineer and BIM specialist whose research integrates Building Information Modeling (BIM), Artificial Intelligence (AI), and automation technologies to advance construction engineering and management. His work focuses on enhancing construction site efficiency, digitalizing bridge inspection processes, and improving safety training through intelligent systems. With expertise in structural analysis, BIM development, and programming (C#, Python, Revit API, AutoCAD API), his research aims to transform traditional workflows into smart, data-driven solutions for sustainable and safe construction environments. He has contributed to advancing real-time data integration, predictive modeling for reinforced concrete (RC) structures, and automation in bridge assessment using machine learning. Amr’s scholarly impact is reflected in his early academic recognition, having 1 citation, 1 h-index, and 0 i10-index on Google Scholar, with research visibility growing rapidly. His publications are featured in Advances in Structural Engineering and Applied Sciences journals. He continues to explore the intersection of BIM and AI for next-generation construction technologies, positioning himself as an emerging researcher dedicated to automation, visualization, and intelligent infrastructure systems. His innovative contributions and growing influence in structural informatics and construction automation make him a deserving recipient of the Best Researcher Award.

Publication Profile

Featured Publications

Ashmawi, A., Nguyen, P., & Jawdhari, A. (2025). State-of-the-art review of machine learning applications for bridge inspections. Advances in Structural Engineering, 13694332251381220.

Nichols, L., Ashmawi, A., & Nguyen, P. (2025). Digitalizing bridge inspection processes using Building Information Modeling (BIM) and Business Intelligence (BI). Applied Sciences, 15(20), 10927.

Ashmawi, A., Nguyen, P., & Jawdhari, A. (2025). Enhancing construction safety training using artificial intelligence: Existing applications and future directions. Under publication.

Ashmawi, A., & Nguyen, P. (2025). Leveraging BIM for automated fire safety code compliance: A comprehensive review. Under review.