Chen Yang | Engineering | Research Excellence Award

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Prof. Chen Yang | Engineering | Research Excellence Award

School of Energy and Power, Chongqing University  |  China

Prof. Chen Yang  research centers on advanced energy systems, renewable energy utilization, and thermal power engineering, with strong emphasis on modeling, optimization, and dynamic control of complex thermo-energy systems, supported by a research record of 1,004 citations across 868 documents, 98 publications, and an h-index of 18. His contributions span ultra-supercritical circulating fluidized bed boilers, nuclear power reactor secondary systems, compressed air energy storage, and hybrid solid oxide fuel cell–gas turbine systems, advancing the efficiency, reliability, and safety of large-scale power generation. He has developed multi-physics and multi-scale reduced-order modeling techniques to address nonlinear dynamics, uncertainty, cooperative simulation, and system stability challenges, enabling enhanced operational performance under transient and abnormal working conditions. His work integrates mechanistic models with artificial intelligence, including neural networks and time-series methods, to achieve online simulation, intelligent prediction, fault early warning, and predictive control in energy systems. He has also contributed to thermodynamic coupling analysis, waste heat utilization strategies, and multi-objective optimization frameworks for green energy systems. Through these innovations, his research significantly supports sustainable power technology development, promotes intelligent and resilient energy infrastructures, and contributes to low-carbon energy transformation and modern energy system advancement.

Citation Metrics (Scopus)

1200

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0

Citations
1004

Documents
98

h-index
18

🟦 Citations    🟥 Documents    🟩 h-index


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Featured Publications

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.

 

 

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.

 

Mehran Pourgholi | Engineering | Best Researcher Award

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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

 

Manença Cristiano Nhanga| Materiais| Excellence in Research Award

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Mr.Manença Cristiano Nhanga |Materiais| Excellencein Research Award

Researcher staff at Púnguè University,Mozambique.
Manença Cristiano Nhanga is a researcher and staff member at Púnguè University, Mozambique. His academic and research interests focus on areas related to engineering, environmental sciences, and sustainable development. With a strong commitment to advancing knowledge and innovation, he actively contributes to research projects and academic initiatives at the university.
professional profiles📖

Orcid

Education 🎓

Púnguè University, Mozambique (2020 – 2024)Degree: Bachelor’s in Physics Teaching with a focus on Renewable Energy.Distinction: Best student in the Faculty of Exact and Technological Sciences with an average of 15/20.University of Minho, Portugal (Feb – June 2024)Conducted a research project on “Evaluation of Heavy Metals Content in Plastic Bags Used as Part of Food Cooking Containers by the Mozambican Community” under the guidance of Prof. Dr. Maria Dulce Geraldo, Prof. Dr. Manuel Filipe Costa, and Prof. Dr. Sérgio Nhapulo.Global Inclusive Society, Brazil (2023)Certified in International Relations, Cooperativism, Geopolitics, and Public Speaking.Mopeia Secondary School, Zambezia (2014-2018)Achieved the best academic performance and was exempted from the national examination in 10th grade.

work Experience💼

University of Minho, Portugal (Feb – June 2024)Poster Presentation at VII ETCAQ: Evaluation of Zn in Plastic Bags used as Food Containers in Mozambique.Book Chapter Author: Science Education and Sustainability in Hands-On Science 2024.Article Author: Evaluation of Heavy Metals in Plastic Bags used as Improvised Food Cooking Covers: A Case Study from Mozambique (Sustainability Journal 2025, 17, 964).Conference Participation:VII Meeting of Chemical Characterization and Analysis Techniques (June 7, 2024)Catalysis in Industry Lecture by Prof. Pham Thanh Huyen from Hanoi University of Science and Technology (June 20, 2024)Science Fair Jury Member at Colégio do Minho (May 23, 2024)Oral Presentation at the 21st Annual International Hands-On Science Conference 2024 in Goiás, Brazil.Electro Expresso, Lda [Assistant]Worked in service, maintenance, and logistics.Global Inclusive Society [Assistant Teacher] (2023)Taught English at intermediate and pre-advanced levels.EISA-JOINT Mozambique [Election Representative, Luabo] (2019)

Research Focus

Nhanga’s research primarily explores:Environmental Sustainability and Heavy Metal ContaminationRenewable Energy Applications in Physics EducationScience Education and Sustainable DevelopmentMaterial Safety in Food PackagingHis work addresses societal challenges in Mozambique, particularly regarding food safety, environmental impact, and education in underdeveloped regions.

Awards & Honors🏆 

Best Student in Physics Course – Púnguè University (2024)
🏆 Best Academic Performance – University of Minho (ERASMUS+ ICM, 2024)
🏆 Best Academic Performance in Secondary School – Mopeia Secondary School (2018)

Conclusion✅

Based on his academic excellence, research achievements, and international collaboration, Manença Cristiano Nhanga is a highly suitable candidate for the Excellence in Research Award. By enhancing his publication record, research funding, and interdisciplinary studies, he can further establish himself as a leading scholar in environmental and material sciences.

📚Publications to Noted

  • Nhanga, M. C., Geraldo, D., Nhapulo, S. L., João, A. F., Carneiro, J., & Costa, M. F. M. (2025). Evaluation of Heavy Metal Content in Plastic Bags Used as Improvised Food Cooking Covers: A Case Study from the Mozambican Community. Sustainability, 17, 964.

  • Nhanga, M. C. (2024). Evaluation of Heavy Metal Content in Plastic Bags Used as Part of Food Cooking Containers: A Socio-educational Sustainability Perspective in Mozambique. In Science Education and Sustainability (pp. XX-XX). ISBN 978-84-8158-971-9.