Mr. Junde Lu | Artificial Neural Networks | Best Researcher Award

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Mr. Junde Lu | Artificial Neural Networks | Best Researcher Award

Beijing Information Science and Technology University | China

Mr. Junde Lu is a promising early-career researcher specializing in optical communication systems and signal processing, with a focus on developing efficient equalization algorithms for high-speed data transmission. His research interests center around enhancing the performance and reliability of optical communication links through advanced digital signal processing and AI-empowered equalization methods. He has contributed to the design of low-complexity receiver-side equalizers and has explored the potential of machine learning in nonlinear compensation for coherent optical systems. His scholarly contributions have been published in reputable international journals and conferences, particularly within the fields of photonics and communication technology. Junde Lu has authored and co-authored several scientific documents, with a citation record demonstrating growing recognition in his domain. According to Scopus and Google Scholar metrics, his academic record includes 13 research documents, 1 citation, and an h-index of 1, highlighting his emerging influence in optical communication research. His collaborative works with distinguished researchers underscore his commitment to advancing next-generation high-speed optical transmission technologies.

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Scopus

Featured Publications

Lu, J., Sun, Y., Qin, J., & Lu, G.-W. (2025). A low-complexity receiver-side lookup table equalization method for high-speed short-reach IM/DD transmission systems. Photonics.

Chen, L., Sun, Y., Shi, J., Lu, J., & Qin, J. (2025). Exploring 400 Gbps/λ and beyond with AI-accelerated silicon photonic slow-light technology. Photonics.

Dr. Hem Bahadur Motra | Rock Mechanics| Excellence in Research Award

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Dr. Hem Bahadur Motra | Rock Mechanics| Excellence in Research Award

University of Kiel | Germany

Dr. Hem Bahadur Motra is a distinguished researcher in the field of geomechanics, rock mechanics, and structural reliability with a strong interdisciplinary background bridging engineering computing, uncertainty modeling, and geostatistics. His research primarily focuses on reliable engineering computation, structural reliability, risk and hazard analysis, and quality evaluation of numerical, mathematical, and experimental models and methods. Dr. Motra has made significant contributions to rock physics, reservoir characterization, and the study of elastic and seismic anisotropy of rocks under extreme pressure and temperature conditions. His work also encompasses advanced uncertainty modeling in structural and geotechnical engineering, enhancing the understanding of rock behavior and material properties under variable environmental influences. He has an impressive academic record with 47 Scopus-indexed publications, accumulating 625 citations from 537 documents and an h-index of 14. On Google Scholar, his research impact is even broader, with 899 citations, an h-index of 16, and an i10-index of 23, reflecting the depth and influence of his scholarly contributions. Dr. Motra’s research excellence lies in combining experimental, computational, and probabilistic approaches to assess material behavior, measurement uncertainty, and geomaterial modeling, contributing to both fundamental understanding and industrial applications.

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Featured Publications

Motra, H. B., Hildebrand, J., & Dimmig-Osburg, A. (2014). Assessment of strain measurement techniques to characterise mechanical properties of structural steel. Engineering Science and Technology, an International Journal, 17(4), 260–269.

Ji, S., Li, L., Motra, H. B., Wuttke, F., Sun, S., Michibayashi, K., & Salisbury, M. H. (2018). Poisson’s ratio and auxetic properties of natural rocks. Journal of Geophysical Research: Solid Earth, 123(2), 1161–1185.

Khalifeh, M., Saasen, A., Hodne, H., & Motra, H. B. (2019). Laboratory evaluation of rock-based geopolymers for zonal isolation and permanent P&A applications. Journal of Petroleum Science and Engineering, 175, 352–362.

Motra, H. B., & Stutz, H. H. (2018). Geomechanical rock properties using pressure and temperature dependence of elastic P- and S-wave velocities. Geotechnical and Geological Engineering, 36(6), 3751–3766.

Motra, H. B., Hildebrand, J., & Wuttke, F. (2016). The Monte Carlo Method for evaluating measurement uncertainty: Application for determining the properties of materials. Probabilistic Engineering Mechanics, 45, 220–228.

Dr. Friba Nurmukhamma | Medicine | Best Researcher Award

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Dr. Friba Nurmukhamma | Medicine | Best Researcher Award

Khoja Akhmet Yassawi International Kazakh-Turkish University | Kazakhstan

Dr. Friba NurmukhammadNasrullakyzy is a cardiologist, senior researcher, and PhD scholar specializing in cardiovascular pathology, with a particular focus on coronary artery disease (CAD), stenting, and post-coronary artery bypass grafting (CABG) outcomes. Her research explores the mechanisms of high residual platelet reactivity (HRPR) and dyslipidemia, contributing to improved treatment algorithms and predictive models aimed at reducing mortality in patients with complex cardiovascular conditions. Dr. Friba’s innovative work integrates clinical insights with advanced diagnostic methodologies and personalized therapeutic approaches, emphasizing non-statin therapies, platelet reactivity modulation, and functional diagnostics in cardiology. She has authored multiple peer-reviewed publications indexed in Scopus and other scientific databases, reflecting a growing international research presence. Her Scopus h-index is 3, and her research impact is further supported by citations across both Scopus and Google Scholar databases. Dr. Friba’s current projects involve developing mortality prediction scales and individualized treatment algorithms for patients with HRPR, aiming to advance precision medicine in cardiology. Her scientific contributions underscore her commitment to translational cardiovascular research and her role in fostering evidence-based practices within clinical cardiology.

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Scopus | ORCID

Featured Publications

Mussagaliyeva, A., Zhangelova, S., Danyarova, L., Nurmukhammad, F., Kapsultanova, D., Sakhov, O., Rustamova, F., Sugraliyev, A., & Akhmentayeva, D. (2025). Residual platelet reactivity and dyslipidemia in post-CABG patients undergoing repeat revascularization: Insights from Kazakhstan. Diseases, 13(11), 365.

Nurmukhammad, F. N., Zhangelova, S. B., & Kapsultanova, D. A. (2025). Non-statin therapy in patients with elevated LDL-C and high platelet reactivity: A narrative review. Medical Journal of Malaysia, 80(2), 258–265.

Zhangelova, S. B., Nurmukhammad, F. N., & Nurdinov, N. (2023). High residual platelet reactivity as a predictor of atherothrombosis in patients with coronary heart disease. Science and Healthcare, 25(3), 25–31.

Mussagaliyeva, A., Zhangelova, S., Nurmukhammad, F., & Kapsultanova, D. (2025). Residual platelet reactivity and dyslipidemia in post-CABG patients: Preprint insights from Kazakhstan. Preprints, 2025(09), 2498.

Prof. Dr. Abdel-Aziz Sharabati | Business Intelligence | Best Researcher Award

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Prof. Dr. Abdel-Aziz Sharabati | Business Intelligence | Best Researcher Award

Middle East University | Jordan

Prof. Dr. Abdel-Aziz Ahmad Sharabati is a distinguished scholar in Business Administration, specializing in intellectual capital, total quality management, corporate social responsibility, supply chain management, and digital business strategies. His research bridges management theory and practical applications, focusing on how digital transformation, innovation, and sustainability drive organizational performance across industries. He has made extensive academic contributions with over 80 publications in reputed international journals and more than 30 conference presentations globally. His work often integrates qualitative and quantitative methodologies to explore emerging trends such as artificial intelligence, digital marketing, and blockchain in business ecosystems. Prof. Sharabati’s research impact is reflected in his strong citation metrics, including 1,179 Scopus citations across 56 documents with an h-index of 18, and 6,243 Google Scholar citations with an h-index of 28 and an i10-index of 50, highlighting his sustained scholarly influence and interdisciplinary reach.

Research Profile

Scopus | ORCID | Google Scholar

Featured Publications

Aristovnik, A., Keržič, D., Ravšelj, D., Tomaževič, N., & Umek, L. (2020). Impacts of the COVID-19 pandemic on life of higher education students: A global perspective. Sustainability, 12(20), 8438.

Sharabati, A. A. A., Jawad, S. N., & Bontis, N. (2010). Intellectual capital and business performance in the pharmaceutical sector of Jordan. Management Decision, 48(1), 105–131.

Sharabati, A. A. A., Ali, A. A. A., Allahham, M. I., Hussein, A. A., & Alheet, A. F. (2024). The impact of digital marketing on the performance of SMEs: An analytical study in light of modern digital transformations. Sustainability, 16(19), 8667.

Al-Haddad, S., Sharabati, A. A. A., Al-Khasawneh, M., Maraqa, R., & Hashem, R. (2022). The influence of corporate social responsibility on consumer purchase intention: The mediating role of consumer engagement via social media. Sustainability, 14(11), 6771.

Atieh Ali, A. A., Sharabati, A. A. A., Allahham, M., & Nasereddin, A. Y. (2024). The relationship between supply chain resilience and digital supply chain and the impact on sustainability: Supply chain dynamism as a moderator. Sustainability, 16(7), 3082.

Prof. Zhiguo Zhao | Machine Learning | Best Researcher Award

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Prof. Zhiguo Zhao | Machine Learning | Best Researcher Award

Professor | Huaiyin Institute of Technology | China

Prof. Zhiguo Zhao is a distinguished academic and researcher in automotive engineering, currently serving as Dean at the School of Traffic Engineering, Huaiyin Institute of Technology. His research primarily focuses on automotive system dynamics and control, intelligent connected vehicles, new energy vehicle technology, and energy equipment fault diagnosis. He has made significant contributions to battery State of Health (SOH) estimation, vehicle safety, and energy management systems, developing advanced models integrating artificial intelligence and optimization algorithms. Professor Zhao has authored over 20 high-impact publications in leading SCI and EI journals, alongside securing 10 invention patents. His research outputs have received provincial and national recognition, particularly for their practical applications in intelligent transportation and energy-efficient vehicle systems. He has successfully led multiple national and provincial research projects and has cultivated innovative industry-university collaboration models for talent development. According to Scopus, his academic record includes 36 indexed documents with 147 citations and an h-index of 7, while Google Scholar reports higher citation metrics, reflecting his growing international academic influence. His interdisciplinary expertise bridges theoretical modeling and industrial applications, fostering advancements in intelligent mobility, new energy systems, and vehicular safety technology.

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Scopus

Featured Publications

Zhao, Z. (2025). Estimation of lithium battery state of health using hybrid deep learning with multi-step feature engineering and optimization algorithm integration. Energies, 18(21), 5849.

Zhao, Z. (2019). Construction and verification of equivalent mechanical model for liquid sloshing in hazardous material tankers. Journal of Huaiyin Institute of Technology, 5, 1–10.

Zhao, Z. (2023). Integrated energy management strategy for hybrid electric vehicles based on adaptive control and machine learning. Journal of Energy Storage, 59, 106781.

Zhao, Z. (2022). Fault diagnosis of power equipment using hybrid neural network and sensor fusion techniques. IEEE Transactions on Industrial Electronics, 69(8), 8123–8134.

Zhao, Z. (2021). Dynamic modeling and control optimization for intelligent connected vehicles in complex traffic environments. Vehicle System Dynamics, 59(4), 613–631.

Assist. Prof. Dr. Hanen Marzouki | Biotechnology | Best Researcher Award

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Assist. Prof. Dr. Hanen Marzouki | Biotechnology | Best Researcher Award

University of Monastir | Tunisia

Dr. Hanen Marzouki is an accomplished Assistant Professor in Biological Sciences from Tunisia, specializing in the study of essential oils, plant extracts, and their biological activities. Her research focuses on the chemical characterization, chromatographic separation, and bioactivity evaluation of natural compounds derived from medicinal and aromatic plants. She has significantly contributed to understanding the biochemical composition, allelopathic potential, and pharmacological properties of essential oils—particularly those of Laurus nobilis L., Eucalyptus species, and Artemisia herba-alba. Her interdisciplinary expertise spans phytochemistry, in vitro propagation, and molecular analysis, integrating traditional botanical knowledge with modern biotechnological and analytical techniques. Dr. Marzouki has collaborated internationally on research exploring supercritical CO₂ extraction, GC/MS profiling, and in silico molecular docking to investigate bioactive substances for potential therapeutic and agricultural applications. Her scholarly impact is reflected in Scopus with 135 citations across 123 documents and an h-index of 4. On Google Scholar, she continues to build an expanding citation base highlighting her contributions to natural product chemistry and sustainable bioresources.

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Scopus

Featured Publications

Marzouki, H., Horchani, M., Chaieb, I., M’Rabet, Y., Ben Jannet, H., & Saadaoui, E. (2025). Chemical characterization, in silico investigations, in vitro evaluation of allelopathic potential and insecticidal activity of Laurus nobilis L. essential oil. Chemistry & Biodiversity.

Piras, A., Marzouki, H., Falconieri, D., Porcedda, S., Gonçalves, M. J., & Salgueiro, L. (2017). Chemical composition and biological activity of volatile extracts from leaves and fruits of Schinus terebinthifolius Raddi from Tunisia. Records of Natural Products, 11(1), 9–16.

Floris, S., Fais, A., Rosa, A., Piras, A., Marzouki, H., & Era, B. (2019). Phytochemical composition and enzyme inhibitory properties of seed extracts from the Washingtonia filifera palm. RSC Advances, 9, 21278.

Marzouki, H., Falconieri, D., Piras, A., & Porcedda, S. (2015). Chemical composition of essential oils from needles of Pinus pinaster from Italy and Tunisia. Asian Journal of Chemistry, 27(7).

Marzouki, H., Khaldi, A., Piras, A., & Marongiu, B. (2009). Biological activity evaluation of the oils from Laurus nobilis of Tunisia and Algeria extracted by supercritical carbon dioxide. Natural Products Research, 23, 230–237.

Mrs. Andsera Adugna Mekonen | Remote Sensing | Young Scientist Award

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Mrs. Andsera Adugna Mekonen | Remote Sensing | Young Scientist Award

University of Naples | Italy

Andsera Adugna Mekonen is an emerging Earth and Environmental Scientist specializing in remote sensing, geoinformatics, and precision agroforestry systems. His research focuses on leveraging drone and satellite imagery for above-ground biomass estimation and sustainable agroforestry ecosystem monitoring. He integrates advanced remote sensing technologies, GIS applications, photogrammetry, and machine learning to improve environmental assessment and agricultural productivity. His expertise extends to UAS-based data acquisition, multispectral and RGB imagery analysis, and the application of artificial intelligence and data science in Earth observation. He has presented his work at leading international conferences, including IEEE MetroAerospace, and contributed to advancements in sustainable land management and ecosystem monitoring. His innovative approach combines Earth observation with AI-driven analytical frameworks to enhance accuracy in biomass modeling and environmental risk assessment. He has authored impactful research in peer-reviewed journals, with a Scopus record of 2 documents and an h-index of 1, and a Google Scholar profile reflecting 59 citations, an h-index of 2, and an i10-index of 1. His contributions demonstrate a growing influence in geospatial and agro-environmental research, emphasizing interdisciplinary integration of technology and sustainability science.

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Featured Publications

Mekonen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in a complex landscape: A case study of the Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586.

Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above-ground biomass estimation in an agroforestry environment by UAS and RGB imagery. In IEEE International Workshop on Metrology for Aerospace, 272–277.

Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-Ground Biomass Prediction in Agroforestry Areas Using Machine Learning and Multispectral Drone Imagery. In IEEE International Workshop on Metrology for Aerospace, 63–68.

Mekonen, A. A., Accardo, D., & Claudia, C. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 26.

Sisay, S. B., Melkamu, M. B., Birhan, B. A., & Mekonen, A. A. (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.

Assist. Prof. Dr. Mohanned M. H. AL-Khafaji | Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Mohanned M. H. AL-Khafaji | Artificial Intelligence | Best Researcher Award

Engineering | University of Technology | Iraq

Dr. Mohanned Mohammed Hussein Al-Khafaji is an accomplished researcher and academic leader in production engineering, specializing in intelligent manufacturing systems, laser material processing, neural network modeling, and fuzzy logic control applications. As Dean of the College of Production Engineering and Metallurgy at the University of Technology, Baghdad, his research integrates computational modeling, automation, and artificial intelligence to enhance production efficiency and precision engineering. He has made significant contributions to the development of computer-controlled manufacturing systems, laser-based material processing, and predictive modeling using advanced algorithms. His work on CO₂ laser processing, neural network-based machining analysis, and hybrid intelligent systems has advanced industrial automation and smart manufacturing processes. Dr. Al-Khafaji’s research also explores mechatronics, robotic systems, and additive manufacturing, emphasizing simulation tools like Abaqus, COMSOL Multiphysics, and MATLAB. His scientific output reflects substantial academic influence, with 15 Scopus-indexed documents, 41 citations from 37 documents, and an h-index of 3. On Google Scholar, he has accumulated 125 citations, an h-index of 6, and an i10-index of 4, underscoring his growing impact in engineering research.

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Featured Publications

Al-Khafaji, M. M. H., & Hubeatir, K. A. (2021). CO2 laser micro-engraving of PMMA complemented by Taguchi and ANOVA methods. Journal of Physics: Conference Series, 1795(1), 012062.

Al-Khafaji, M. M. H. (2018). Neural network modeling of cutting force and chip thickness ratio for turning aluminum alloy 7075-T6. Al-Khwarizmi Engineering Journal, 14(1), 67–76.

Khayoon, M. A., Hubeatir, K. A., & Al-Khafaji, M. M. (2021). Laser transmission welding is a promising joining technology technique – A recent review. Journal of Physics: Conference Series, 1973(1), 012023.

Momena, T. F. A., Mohammed, M. M. H., & Al-Khafaji, M. M. H. (2023). Smart robot vision for a pick and place robotic system. Engineering and Technology Journal, 40(6), 1–15.

Shaker, F., Al-Khafaji, M., & Hubeatir, K. (2020). Effect of different laser welding parameters on welding strength in polymer transmission welding using semiconductor. Engineering and Technology Journal, 38(5), 761–768.*

Dr. Nabil Bachagha | Remote Sensing | Best Researcher Award

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Dr. Nabil Bachagha | Remote Sensing | Best Researcher Award

University of Leeds | United Kingdom

Dr. Nabil Bachagha is a distinguished Research Fellow and global expert in remote sensing, GIS, and deep learning, with significant contributions to digital heritage preservation and archaeological landscape documentation. His interdisciplinary research integrates advanced geospatial technologies, including UAV photogrammetry, terrestrial 3D laser scanning, and machine learning models, to enhance the detection, classification, and conservation of archaeological and cultural heritage sites. A UK Global Talent Visa holder under the Exceptional Talent Route, Dr. Bachagha’s work bridges technology and heritage, focusing on data-driven approaches to protect endangered sites and reconstruct ancient civilizations through digital innovation. His expertise spans ENVI, ArcGIS, QGIS, and Earth Engine applications, combined with proficiency in Python, R, MATLAB, and JavaScript for geospatial analytics and automated system development. With over 430 citations from 374 documents in Scopus (h-index: 6) and 675 citations in Google Scholar (h-index: 8, i10-index: 7), Dr. Bachagha’s research demonstrates strong academic influence and global recognition. His projects, such as the “One Belt, One Road Heritage Protection” and “Endangered Wooden Architecture Programme,” exemplify his commitment to integrating AI, remote sensing, and geospatial intelligence in cultural heritage management.

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Featured Publications

Bachagha, N., Wang, X., Lasaponara, R., Luo, L., & Khatteli, H. (2020). Remote sensing and GIS techniques for reconstructing the military fort system of Roman boundary (Tunisia section) and identifying archaeological sites. Remote Sensing of Environment.

Bachagha, N., Luo, L., Wang, X., Masini, N., Tababi, M., Khatteli, H., & Lasaponara, R. (2020). Mapping the Roman water supply system of the Wadi el Melah Valley in Gafsa, Tunisia, using remote sensing. Sustainability.

Luo, L., Wang, X., Guo, H., Lasaponara, R., Zong, X., Masini, N., & Bachagha, N. (2019). Airborne and spaceborne remote sensing for archaeological and cultural heritage applications: A review of the century (1907–2017). Remote Sensing of Environment.

Bachagha, N., Xu, W., Luo, X., Brahmi, M., Wang, X., Souei, F., & Lasaponara, R. (2022). On the discovery of a Roman fortified site in Gafsa, southern Tunisia, based on high-resolution X-band satellite radar data. Remote Sensing.

Bachagha, N., Tababi, M., Selim, G., Shao, W., Xue, Y., Li, W., Bennour, A., Luo, L., Lasaponara, R., & Lao, Y. (2025). Facilitating archaeological discoveries through deep learning and space-based observations: A case study in southern Tunisia. Nature Communications.

Prof. Dr. Dachel Martínez Asanza | Medicine | Best Researcher Award

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Prof. Dr. Dachel Martínez Asanza | Medicine | Best Researcher Award

Professor/ Senior Researcher | University of Medical Sciences of Havana | Cuba

Prof. Dr. Dachel Martínez Asanza is a distinguished Cuban scholar and senior researcher in the field of dental sciences and medical education, recognized for her interdisciplinary expertise in comprehensive dentistry, health promotion, epidemiology, and pedagogical innovation in medical education. Her academic pursuits bridge clinical dentistry with public health, emphasizing preventive oral care, biopsychosocial health management, and the integration of digital and natural medicine within community health frameworks. A full professor at the University of Medical Sciences of Havana, Dr. Asanza has made substantial contributions to advancing dental education through work-based learning methodologies and curriculum development in health sciences. Her research explores the intersection of technology, digital health, and education, reflecting a deep commitment to enhancing healthcare delivery and educational practices in dentistry. With a Scopus record of 26 indexed publications, over 143 citations from 107 documents, and an h-index of 7, alongside Google Scholar metrics of 371 total citations, an h-index of 11, and an i10-index of 12, Dr. Asanza’s scholarly impact is widely recognized. Her works are featured in reputed international journals, often addressing themes such as digital health adoption, green innovation, and AI applications in healthcare.

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Featured Publications

  • Golmankhaneh, A. K., Tunç, S., Schlichtinger, A. M., & Martínez Asanza, D. (2024). Modeling tumor growth using fractal calculus: Insights into tumor dynamics. Biosystems, 235, 105071.

  • Kamel Mouloudj, A. B., Bouarar, A. C., Martínez Asanza, D., & Linda, M. (2023). Factors influencing the adoption of digital health apps: An extended technology acceptance model (TAM). Integrating Digital Health Strategies for Effective Administration, 116–132.

  • Martínez Asanza, D. (2018). Traditional teaching in the 21st century? Neuronum Magazine, 4(1), 99–106.

  • Martínez-Asanza, D. (2021). Regarding work-based learning, a guiding principle of Cuban medical education. FEM: Journal of the Medical Education Foundation, 24(6), 325–325.

  • Njoku, A., Mouloudj, K., Bouarar, A. C., Evans, M. A., & Martínez Asanza, D. (2024). Intentions to create green start-ups for collection of unwanted drugs: An empirical study. Sustainability, 16(7), 2797.