Xuemei Wang | Metallic Materials | Best Researcher Award

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Xuemei Wang | Metallic Materials | Best Researcher Award

Dr. Xuemei Wang at Shanghai University | China

Xuemei Wang’s research centers on understanding and improving the corrosion resistance of metallic materials in complex marine environments, with a particular focus on copper–nickel alloys and underwater welding technologies. Her work bridges materials science, electrochemistry, and mechanical engineering, aiming to enhance the durability and performance of metals used in marine and offshore applications. During her master’s studies at Qilu University of Technology, she investigated the corrosion resistance of EH40 steel underwater wet welded joints, resulting in two SCI-indexed publications and participation in three patent designs. Currently pursuing her Ph.D. in Materials Science and Engineering at Shanghai University, Wang’s doctoral research explores the local corrosion mechanisms of copper–nickel alloys using advanced filament electrode techniques, seeking to elucidate corrosion behavior under varying environmental and electrochemical conditions. Her ongoing studies have already produced four SCI papers and one EI-indexed paper, demonstrating her significant contribution to corrosion science and materials engineering. Beyond her academic achievements, her research holds strong industrial relevance, providing theoretical and experimental foundations for the development of corrosion-resistant materials critical to shipbuilding, offshore structures, and marine energy systems. By integrating surface analysis, experimental modeling, and advanced simulation methods, Wang adopts a comprehensive approach to studying localized corrosion phenomena at microstructural and electrochemical levels. Her work not only contributes to academic advancement but also supports global sustainability goals by promoting eco-friendly corrosion control strategies and improving material longevity in marine environments. Through her persistence, interdisciplinary vision, and commitment to innovation, Xuemei Wang continues to play a vital role in advancing corrosion science and developing practical solutions for marine materials engineering.

Profile:  Orcid

Featured Publications 

Taame Abraha Berhe | Materials Science | Best Researcher Award

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Taame Abraha Berhe | Materials Science | Best Researcher Award

Assist Prof. Dr. Taame Abraha Berhe at Adigrat university | Ethiopia

Dr. Taame Abraha Berhe is a distinguished researcher and academic specializing in applied and theoretical chemistry, with a strong focus on quantum chemistry, materials and energy chemistry, and materials science and engineering. He serves as an Assistant Professor at Adigrat University, Ethiopia, where he has been actively engaged in teaching and research since 2017. Currently, he is a Postdoctoral Researcher at National Taiwan University, where his work extends into advanced material characterization and surface modification technologies. Dr. Berhe earned his Ph.D. from the National Taiwan University of Science and Technology, where he also gained hands-on experience in synchrotron radiation research at the Taiwan and Japanese Photonic Sources, enriching his expertise in advanced experimental and computational methods. His research contributions aim to bridge fundamental chemistry with applied material innovations for sustainable energy and technological advancement. Over the years, he has held several academic leadership positions, including Head of the Department of Chemistry and Dean of the College of Natural and Computational Science at Adigrat University, reflecting his commitment to scientific education and institutional development. Dr. Berhe’s scholarly influence extends internationally through his service as a reviewer for multiple reputable journals, including Advances in Science, Technology and Engineering Systems Journal, Materials Science Research India, and Journal of Food Composition and Analysis. His dedication to quality research and peer review has been recognized with multiple awards, such as the Certificate of Excellence in Reviewing from Current Journal of Applied Science and Technology and commendations from RSC Advances and other scientific publishers. Dr. Berhe’s research vision emphasizes the integration of physical chemistry principles and material science to drive innovation in energy systems, catalysis, and sustainable materials for global scientific and industrial progress.

Profile:  GoogleScholar

Featured Publications 

Saeed Behseresht | Thermoplastic composites | Best Researcher Award

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Saeed Behseresht | Thermoplastic composites | Best Researcher Award

Mr. Saeed Behseresht at New Mexico State University | United States

Dr. Saeed Behseresht is a dedicated Mechanical Engineer and researcher currently pursuing his Ph.D. in Mechanical Engineering at New Mexico State University (NMSU), where he also earned his master’s degree with a perfect GPA of 4.0/4.0. His academic foundation includes a Bachelor’s in Mechanical Engineering from Hakim Sabzevari University (HSU) and a Master’s in Applied Mechanics of Solids from Shahid Beheshti University (SBU) in Iran. His research focuses on Metal Additive Manufacturing (AM), specializing in Wire Arc Additive Manufacturing (WAAM) process control, machine learning (ML) and reinforcement learning (RL) for AM process monitoring, digital twin development, defect detection, and finite element analysis (FEA) of metal and polymer AM. As a Graduate Research Assistant at NMSU, Dr. Behseresht has developed hybrid physical-virtual digital twins and ML-based process control frameworks for optimizing AM performance, integrating high-speed imaging, simulation, and predictive modeling. His work includes designing constitutive material models and implementing user subroutines in Abaqus to advance predictive failure analysis of AM components. He has published several peer-reviewed journal and conference papers in leading platforms such as Metals, Journal of Materials, and Metrology, and actively contributes as a peer reviewer for reputed journals including the International Journal of Advanced Manufacturing Technology and Archives of Computational Methods in Engineering. Beyond research, he teaches Solid Mechanics Lab and Engineering Analysis as a Graduate Teaching Assistant, guiding undergraduate students through practical applications of mechanical engineering principles. His technical expertise spans Abaqus, Ansys, SolidWorks, Catia, Python, and Fortran, complemented by strong analytical and strategic skills. Dr. Behseresht’s research achievements have earned him the Roy R. Hilbrand Endowed Scholarship and the Grad Success Scholarship at NMSU. His scholarly impact is evidenced by 93 citations, an h-index of 5, and an i10-index of 5, reflecting his growing influence in the field of advanced manufacturing and computational mechanics.

Profile:  GoogleScholar

Featured Publications 

Mahdi Ghafouri Vayghan | Microwave Systems | Best Researcher Award

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Mahdi Ghafouri Vayghan | Microwave Systems | Best Researcher Award

Mr. Mahdi Ghafouri Vayghan at Ural Federal University | Russia

Mahdi Ghafouri Vayghan is an emerging researcher in antenna and microwave engineering, currently pursuing his Ph.D. in Antenna, Microwave Systems, and their Technologies at Ural Federal University (URFU), Yekaterinburg, Russia, under the supervision of Professor Sergey Shabunin. His doctoral dissertation focuses on the design, simulation, and fabrication of microwave sensors based on metamaterials, contributing to advancements in compact, high-sensitivity sensor technologies. He earned his Master’s degree in Telecommunication Engineering (Field & Wave) from Tarbiat Modares University (TMU), Tehran, Iran, where he graduated with distinction and conducted research on metasurface antennas for 5G base station communication systems. His key research interests include microwave sensors, electromagnetic Green’s functions, antennas for 5G/6G systems, passive and active microwave devices, terahertz technologies, graphene, metamaterials, and particle accelerators. Mahdi has authored and co-authored several journal and conference papers in reputable outlets such as Optik and Scientific Reports, as well as IEEE conferences, highlighting his expertise in metamaterial-based sensors and electromagnetic field analysis. His publications demonstrate his growing impact in the field, with 3 citations, an h-index of 1, and an i10-index of 0. Recognized for academic excellence, he has received the Russian Government Scholarship (2023–2027) and was selected among Exceptional Talents at TMU, ranking second among MSc graduates in Telecommunication Engineering. His technical proficiency spans CST Microwave Studio, HFSS, ADS, MATLAB, and Antenna Magus, allowing him to integrate theoretical modeling with practical design and fabrication. Fluent in Persian, Turkish, English, and Russian, Mahdi actively collaborates on international research projects, continually advancing innovations in antenna design, metamaterial applications, and microwave sensing technologies.

Profile: GoogleScholar

Featured Publications 

Wenyan Wu | Modeling | Best Researcher Award

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Wenyan Wu | Modeling | Best Researcher Award

Dr. Wenyan Wu at Guangdong University of Technology | China

Dr. Wenyan Wu is an emerging researcher whose work focuses on the intersection of artificial intelligence, multimodal learning, and intelligent systems with applications in emotion recognition, sentiment analysis, and human-computer interaction. Since creating her ORCID record in August 2022, Dr. Wu has actively contributed to advancing research in cross-modal data analysis, integrating deep learning frameworks with cognitive and affective computing techniques. Her recent publication, “Modality-Enhanced Multimodal Integrated Fusion Attention Model for Sentiment Analysis” (Applied Sciences, 2025), introduces a novel attention-based fusion approach to improve sentiment analysis accuracy by effectively capturing inter-modal dependencies across text, audio, and visual cues. In “Collaborative Analysis of Learners’ Emotional States Based on Cross-Modal Higher-Order Reasoning” (Applied Sciences, 2024), Dr. Wu explores emotion-aware learning environments, presenting innovative reasoning mechanisms for identifying and analyzing learners’ affective states to enhance adaptive education systems. Her research on “Mask-Wearing Detection in Complex Environments Based on Improved YOLOv7” (Applied Sciences, 2024) demonstrates her interdisciplinary expertise, combining computer vision and deep neural networks to address real-world safety monitoring challenges. Earlier, her foundational study, “A Novel Method for Cross-Modal Collaborative Analysis and Evaluation in the Intelligence Era” (Applied Sciences, 2022), laid the groundwork for her later research by proposing an integrated model for data collaboration across modalities in intelligent environments. Dr. Wu’s scholarly output reflects her strong analytical and technical acumen, emphasizing multimodal integration, attention mechanisms, and deep learning optimization. Her contributions not only advance theoretical understanding but also provide practical frameworks for developing emotionally intelligent and context-aware AI systems, bridging the gap between computational models and human-centered design in modern intelligent applications.

Profile: Orcid 

Featured Publications 

Vassilis Kostopoulos | Polymer Matrix Composites | Best Researcher Award

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Vassilis Kostopoulos | Polymer Matrix Composites | Best Researcher Award

Prof. Vassilis Kostopoulos at University Of Patras | Greece

A distinguished scholar in mechanical and aerospace engineering, Professor Vassilis Kostopoulos has made pioneering contributions to the fields of applied mechanics, composite materials, and structural health monitoring. He has served as Professor and former Director of the Applied Mechanics & Vibrations Laboratory (2003–2024) at a leading European university, with visiting appointments at major international institutions, including the University of Delaware (USA) and George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureş (Romania). His expertise spans design, analysis, and optimization of lightweight composite structures, non-destructive evaluation, nano-engineering, aerospace structures under extreme conditions, and additive manufacturing. A key contributor to European and international research programs, he has coordinated or participated in over 85 research projects funded by organizations such as the EU, ESA, EDA, EDF, NSF, and USAF. His extensive academic output includes 345 publications, 301 conference presentations, 7 books, 21 book chapters, and numerous technical reports, achieving 6,304 citations from 5,234 documents with an h-index of 40. He has supervised 35 Ph.D. and 185 M.Sc. theses and co-organized 61 international conferences. His leadership roles include membership in the Clean Aviation Joint Undertaking, Advisory Council for Aviation Research and Innovation in Europe (ACARE), and the European Society for Composite Materials (ESCM), where he also served as President. He is an editorial board member for several international journals and an evaluator for research programs across Europe. His research achievements have been recognized with multiple international awards, including the 1st Senior Scientist Award at TRA-VISIONS 2020, ESA Aerospace Challenge distinctions, and Innovation Awards in aerospace and space engineering, reflecting his enduring impact on advanced materials and aeronautical research.

Profile: Scopus | Orcid | GoogleScholar 

Featured Publications 

Attia, S., Eleftheriou, P., Xeni, F., Morlot, R., Ménézo, C., Kostopoulos, V., Betsi, M., & others. (2017). Overview and future challenges of nearly zero energy buildings (nZEB) design in Southern Europe. Energy and Buildings, 155, 439–458.

Kostopoulos, V., Baltopoulos, A., Karapappas, P., Vavouliotis, A., & Paipetis, A. (2010). Impact and after-impact properties of carbon fibre reinforced composites enhanced with multi-wall carbon nanotubes. Composites Science and Technology, 70(4), 553–563.

Loutas, T. H., Roulias, D., Pauly, E., & Kostopoulos, V. (2011). The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery. Mechanical Systems and Signal Processing, 25(4), 1339–1352.

Karapappas, P., Vavouliotis, A., Tsotra, P., Kostopoulos, V., & Paipetis, A. (2009). Enhanced fracture properties of carbon reinforced composites by the addition of multi-wall carbon nanotubes. Journal of Composite Materials, 43(9), 977–985.

Loutas, T. H., Sotiriades, G., Kalaitzoglou, I., & Kostopoulos, V. (2009). Condition monitoring of a single-stage gearbox with artificially induced gear cracks utilizing on-line vibration and acoustic emission measurements. Applied Acoustics, 70(9), 1148–1159.

Olagunju Johnson Adetuwo | Polymer Matrix composites | Excellence in Research Award

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Olagunju Johnson Adetuwo | Polymer Matrix composites | Excellence in Research Award

Dr. Olagunju Johnson Adetuwo at Olusegun Agagu University of Science and Technology Okitipupa Ondo State | Nigeria

Dr. Olagunju Johnson Adetuwo is a highly motivated and experienced Food Security and Nutrition Specialist with a strong background in food microbiology, biotechnology, and humanitarian development. He is currently pursuing a Ph.D. in Food and Industrial Microbiology at Olusegun Agagu University of Science and Technology, Okitipupa, where he is a recipient of the prestigious Vice-Chancellor’s Ph.D. Scholarship Award for Outstanding Students. He holds a Master’s Degree in Industrial Microbiology from Adekunle Ajasin University, a Bachelor’s Degree in Microbiology from the University of Benin, and a Nigeria Certificate in Education from Adeyemi College of Education, specializing in Biology and Chemistry. With extensive professional experience in academia, research, and public service, Dr. Adetuwo serves as a Food Security and Biotechnology Researcher at Olusegun Agagu University of Science and Technology and Adekunle Ajasin University, focusing on sustainable food production, food safety, and biotechnology innovations. He also works as a Project Coordinator at the Ondo State Ministry of Health and Social Welfare, managing initiatives related to WASH, livelihoods, and disability-inclusive development. A dedicated scholar and peer reviewer, he is affiliated with several professional organizations, including the Nigerian Society for Microbiology, American Society of Clinical Oncology, and Society for Industrial Microbiology and Biotechnology, and has earned multiple Awards of Excellence in Peer Reviewing from international journals. Beyond academia, he contributes to community development as a Pastor and Church Leader with the Deeper Life Bible Ministry and serves as an Examiner and Supervisor for national examinations.

Profile: Orcid  | Linkedin

Featured Publications 

Olagunju Johnson, A., & Ogundana, F. N. (2025, August 22). Optimization of substrate and fermentation conditions for mycoprotein production from Pleurotus ostreatus (oyster mushroom) cultivated on sugarcane straw and cassava peels in Okitipupa, Nigeria [Preprint]. bioRxiv.

Olagunju Johnson, A. (2025, August 12). Phenotypic profiling, comparative analysis of nutritional compositions and antioxidant potential of Pleurotus ostreatus (oyster mushroom) cultivated on different agricultural wastes [Preprint]. bioRxiv.

Olagunju Johnson, A., Adegbehingbe, K. T., & Omodara, T. R. (2023, September 29). Safety concerns on microbes associated with fresh and smoked fish sold in Igbokoda Fish Market, Nigeria. Journal of Advances in Microbiology, 23(10758).

Adegbehingbe, K. T., Olagunju Johnson, A., & Omodara, T. R. (2023, August 22). Evaluation of Saccharomyces cerevisiae improved strains potential in the bioethanol production from bagasse. Biotechnology Journal International, 27(5693).

Olagunju Johnson, A. (2023, May 4). Health benefits of energy-rich natural plants. In Health & Fitness.

Yung Hui Huang | Radiological Sciences | Best Researcher Award

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Yung Hui Huang | Radiological Sciences | Best Researcher Award

Prof. Yung Hui Huang at I-Shou university | Taiwan

Yung-Hui Huang  is a distinguished researcher in Medical Imaging and Radiological Sciences at I-Shou University, Taiwan. He earned his Ph.D. (2008) and M.S. (2003) from National Yang-Ming University, Taiwan, specializing in biomedical imaging and radiological sciences, and holds a B.S. in Electrical Engineering (2001) from National Taipei University of Technology, Taiwan. Dr. Huang’s research focuses on advanced imaging techniques, medical image analysis, and machine learning applications in radiology, with a particular emphasis on ultrasound, CT, PET, and MRI imaging modalities. He has authored 52 documents, which have been cited 363 times, resulting in an h-index of 9. His publications appear in internationally recognized journals such as Scientific Reports, Healthcare, Sensors, and the Journal of X-Ray Science and Technology, covering topics from prostate cancer detection, liver and breast imaging, COVID-19 classification, to Parkinson’s disease staging and radiation dosimetry. Dr. Huang’s work combines deep learning, fusion feature extraction, and computational imaging techniques to improve diagnostic accuracy and clinical workflow efficiency. He continues to advance medical imaging research through innovative studies, interdisciplinary collaboration, and mentorship of emerging scientists in the field.

Profile: Scopus | Orcid  

Featured Publications 

Lu, N.-H., Wang, C.-Y., Liu, K.-Y., Huang, Y.-H., & Chen, T.-B. (2025). AI-enhanced deep learning framework for pulmonary embolism detection in CT angiography. Bioengineering, 12(10), 1055.

Liu, K.-Y., Lu, N.-H., Huang, Y.-H., Matsushima, A., Kimura, K., Okamoto, T., & Chen, T.-B. (2025). Majority voting ensemble of deep CNNs for robust MRI-based brain tumor classification. Diagnostics, 15(14), 1782.

Wang, Y.-M., Wang, C.-Y., Liu, K.-Y., Huang, Y.-H., Chen, T.-B., Chiu, K.-N., Liang, C.-Y., & Lu, N.-H. (2024). CNN-based cross-modality fusion for enhanced breast cancer detection using mammography and ultrasound. Tomography, 10(12), 145.

Yang, S.-Y., Hsu, S.-Y., Su, Y.-K., Lu, N.-H., Liu, K.-Y., Chen, T.-B., Chiu, K.-N., Huang, Y.-H., & Yeh, L.-R. (2024). Using key predictors in an SVM model for differentiating spinal fractures and herniated intervertebral discs in preoperative anesthesia evaluation. Diagnostics, 14(21), 2456.

Wang, J.-Z., Lu, N.-H., Du, W.-C., Liu, K.-Y., Hsu, S.-Y., Wang, C.-Y., Chen, Y.-J., Chang, L.-C., Twan, W.-H., Chen, T.-B., & Huang, Y.-H. (2023). Classification of color fundus photographs using fusion extracted features and customized CNN models. Healthcare, 11(15), 2228.

Olufisayo Emmanuel Ojo | Environmental effects | Best Researcher Award

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Olufisayo Emmanuel Ojo | Environmental effects | Best Researcher Award

Mr. Olufisayo Emmanuel Ojo at Atmosfair Climate & Sustainability Limited | Nigeria

Mr. Olufisayo Emmanuel Ojo (R.Engr., IEng – UK, MSc, B.Eng (Hons), M.I.E.T, MNSE) is a distinguished Electromechanical and Water Engineer with over 22 years of professional experience in engineering design, project management, and infrastructural development. He currently serves as the General Manager and Team Lead (Nigeria) for atmosfair gGmbH, Germany, where he directs climate carbon mitigation initiatives, including the establishment and management of a large-scale Improved Cook Stove (ICS) production plant in Nigeria. His diverse expertise encompasses the design and supervision of water treatment facilities, civil and electromechanical infrastructures, hydraulic systems, and asset maintenance management, with notable contributions to projects funded by the World Bank, AFD, EBRD, USAID/E-WASH/RTI, and other international development agencies. A certified professional in Public Procurement, Contract Management, and Monitoring & Evaluation, Mr. Ojo has demonstrated exceptional technical leadership in Non-Revenue Water (NRW) management and sanitation transformation programs. Academically, he holds an M.Sc. (Research) in Mechanical Engineering (Summa Cum Laude) from the University of KwaZulu-Natal, an Hons B.Eng in Mechanical and Manufacturing Engineering from the University of Portsmouth, UK, and an HND in Mechanical Engineering from The Polytechnic, Ibadan, Nigeria, while currently pursuing a Ph.D. in Mechanical Engineering and a Doctor of Engineering (D.Eng) in Industrial Engineering in South Africa. A registered engineer with COREN, MNSE, and MIET (UK), Mr. Ojo has co-authored several impactful publications in renewable energy, desalination systems, and sustainable engineering technologies. His research work has garnered 10 citations, an h-index of 2, and an i10-index of 0. Known for his strategic leadership, innovation, and commitment to sustainable development, Mr. Ojo continues to drive transformative engineering solutions that foster environmental efficiency and resilience.

Profile: Orcid | GoogleScholar | Linkedin

Featured Publications 

Ojo, O. E., & Olanrewaju, O. (2024). A review of renewable energy powered seawater desalination treatment process for zero waste. Water, 16(19), 2804.

Ojo, O. E., & Inambao, F. (2024). Additives and blends of biodiesel. Journal of Propulsion Technology, 45(1), 5032–5050.

Ojo, O. E., & Inambao, F. L. (2024). GT-Power for internal combustion engine simulation: A review. Journal of Aeronautical Materials, 44(2), 38–61.

Ojo, O. E., & Inambao, F. (2024). Real-world applications of waste swine oil (pork lard waste) biodiesel: A review. Journal of Aeronautical Materials, 44(2), 38–61.

Ojo, O. E., Ige, O. E., & Inambao, F. L. (2023). A review of seawater membrane desalination. Corrosion and Protection, 51(2), 476–491.

Seyedeh Tina Sefati | Deep Learning | Best Researcher Award

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Seyedeh Tina Sefati | Deep Learning | Best Researcher Award

Dr. Seyedeh Tina Sefati at University of Tabriz | Iran

Tina Sefati is a Ph.D. candidate in Artificial Intelligence at the University of Tabriz and serves as an AI engineer and CEO at SaamDigital Eurasia, leading AI-driven projects across more than ten countries. Her research focuses on deep learning, supervised and unsupervised learning, time series anomaly detection, and generative models, with extensive expertise in CNNs, LSTMs, GANs, Transformers, and GNNs. She holds an MSc in Artificial Intelligence from the University of Tabriz, where she worked on improving spam filtering using game theory, as well as an M.Sc. in MBA and a BSc in Computer Engineering (Software) from Seraj University, with a thesis on solving the Traveling Salesman Problem using Ant Colony Optimization. Tina has over a decade of experience designing, developing, and managing AI-based systems for large organizations such as HepsiBurada and AndME in Turkey, delivering solutions in product recommendation, stock forecasting, credit scoring, intelligent smile design, license plate recognition, and face recognition systems. She has authored 33 publications, which have received 560 citations across 446 documents, reflecting an h-index of 12, demonstrating the impact of her research contributions. Her technical skills span deep learning, machine learning, NLP, image processing, time series analysis, Python, Flask, SQL, Git, and API development. Tina has also contributed to education as a programming and web design instructor and has successfully led AI projects that integrate statistical methods, NLP, and cloud-based architectures for big data analytics. Recognized for her innovation, leadership, and hands-on expertise in AI applications, she continues to advance research and practical AI solutions, bridging academic insights with industry impact.

Profile: Scopus | Orcid | GoogleScholar

Featured Publications 

Sefati, S. S., Arasteh, B., Halunga, S., & Fratu, O. (2025). Adaptive service recommendation in Internet of Things using a reinforcement learning and optimization algorithm. IEEE Transactions on Network and Service Management.

Ul Haq, A., Sefati, S. S., Nawaz, S. J., Mihovska, A., & Beliatis, M. J. (2025). Need of UAVs and physical layer security in next-generation non-terrestrial wireless networks: Potential challenges and open issues. IEEE Open Journal of Vehicular Technology.

Sefati, S. S., Sefati, S. T., Nazir, S., Zareh Farkhady, R., & Obreja, S. G. (2025, October 6). Federated reinforcement learning with hybrid optimization for secure and reliable data transmission in wireless sensor networks (WSNs). Mathematics.

Arasteh, B., Sefati, S. S., Kusetogullari, H., & Kiani, F. (2025, September 12). Generating software architectural model from source code using module clustering. Symmetry.

Sefati, S. S., Arasteh, B., Craciunescu, R., & Comsa, C.-R. (2025, February 12). Intelligent congestion control in wireless sensor networks (WSN) based on generative adversarial networks (GANs) and optimization algorithms. Mathematics.