Zina Boussada | Engineering | Research Excellence Award

Dr. Zina Boussada | Engineering | Research Excellence Award

Company for Petroleum Research and Operations | Tunisia

Dr. Zina Boussada is an emerging researcher in electrical engineering whose work bridges advanced control systems, intelligent automation, renewable energy technologies, and high-performance power electronics. Her scientific contribution focuses on the modeling, optimization, and control of induction motors, photovoltaic systems, and microgrid energy management using intelligent and hybrid computational approaches. She has contributed extensively to sensorless motor control through ANFIS-based strategies, multilevel NPC inverter topologies, stator-flux orientation techniques, and advanced inverter modulation methods, enhancing system efficiency, stability, and predictive performance in industrial and renewable energy applications. Her research extends to photovoltaic cell modeling, hybrid optimization frameworks, exponential smoothing forecasting, diode-clamped inverter strategies, and comparative inverter control techniques, addressing key challenges in modern smart-grid and clean-energy systems. She has collaborated with several research groups and contributed to journals and international conferences in the areas of energy systems, green technologies, and intelligent electrical drives. Her publication record reflects steady scholarly growth, supported by contributions in peer-reviewed journals such as Symmetry, WSEAS Transactions on Systems and Control, the International Journal of Environmental Sciences, and various high-impact conference proceedings. She has also published multiple studies on photovoltaic modeling and multilevel inverter technologies, reinforcing her position within the renewable-energy research community. Her citation metrics indicate increasing academic visibility, with Scopus reporting approximately 490 citations from 482 citing documents, 23 indexed documents, and an h-index of 9. Google Scholar metrics show comparable academic impact, reflecting a growing global readership and recognition for her work in intelligent control and energy-system optimization. Overall, her research trajectory demonstrates strong potential for continued advancement in sustainable energy technologies, intelligent control methodologies, and high-performance electrical systems, positioning her as a promising candidate for the Research Excellence Award.

Publication Profile

Scopus | Orcid 

Featured Publications

Boussada, Z., Omri, B., & Ben Hamed, M. (2025). High-performance sensorless control of induction motor via ANFIS and NPC inverter topology. Symmetry.

Boussada, Z., Omri, B., & Ben Hamed, M. (2025). Data-driven optimization for efficient integration of photovoltaic agents in residential microgrid systems. Euro-Mediterranean Journal for Environmental Integration.

Konstantinos Azis | Engineering | Research Excellence Award

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

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

ScopusGoogle 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.

 

 

Mehran Pourgholi | Engineering | Best Researcher Award

Assist. Prof. Dr. Mehran Pourgholi | Engineering | Best Researcher Award

Islamic Azad University | Iran

Assist. Prof. Dr. Mehran Pourgholi, an accomplished researcher in Civil and Structural Engineering, has made notable contributions to the fields of system identification, structural health monitoring, inverse problems, and stochastic subspace methods. His research focuses on enhancing the reliability of modal analysis and vibration-based damage detection in large-scale structures such as dams and steel buildings. Dr. Pourgholi integrates advanced computational approaches including entropy-based model selection, optimization algorithms, and error analysis frameworks to improve accuracy in structural system modeling. His collaborative work with experts from the University of Tabriz and Islamic Azad University has produced high-impact studies published in leading international journals such as the Journal of Vibration and Control, Mechanical Systems and Signal Processing, and Engineering Reports. According to Google Scholar, Dr. Pourgholi has 77 citations (68 since 2020), an h-index of 4, and an i10-index of 2, while Scopus records 51 citations across 46 documents with an h-index of 3. His influential publications on stochastic subspace identification and modal analysis have advanced understanding of dynamic behavior in civil structures. Recognized for his scholarly excellence, he has been honored with the Best Researcher Award for his significant impact in the field of structural system identification and vibration analysis.

Publication Profile

Scopus | Orcid | Google Scholar 

Featured Publications

Tarinejad, R., & Pourgholi, M. (2018). Modal identification of arch dams using balanced stochastic subspace identification. Journal of Vibration and Control, 24(10), 2030–2044.

Pourgholi, M., Mohammadzadeh Gilarlue, M. M., Vahdaini, T., & Azarbonyad, M. (2023). Influence of Hankel matrix dimension on system identification of structures using stochastic subspace algorithms. Mechanical Systems and Signal Processing, 186, 109893.

Pourgholi, M., Tarinejad, R., Khabir, M. E., & Mohammadzadeh Gilarlue, M. M. (2023). System identification of Karun IV Dam using balanced stochastic subspace algorithm considering the uncertainty of results. Journal of Vibration and Control, 29(23–24), 5342–5356.

Tarinejad, R., Pourgholi, M., & Yaghmaei-Sabegh, S. (2016). Signal processing of dynamic tests results using subspace identification based on orthogonal decomposition technique (SI-ORT). Modares Mechanical Engineering, 15(10), 104–116.

Pourgholi, M., Ghannadi, M., & Gavgani, S. S. (2024). Modal analysis of earthquake records for dams using stochastic subspace based on error analysis. Engineering Reports, 6(8), e12822