Chang Liu | Geochemistry | Best Researcher Award

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Mr. Chang Liu | Geochemistry | Best Researcher Award

Mr. Chang Liu | Geochemistry | China University of Geosciences | China

Mr. Chang Liu is a geoscientist affiliated with the China University of Geosciences (Beijing), whose work centers on mineral resources, fluid evolution in ore deposits, and geomechanical processes in earth systems; he earned his doctoral education in earth sciences (specializing in petrology, mineralogy and geochemistry) and has since built a profile combining field investigations, laboratory analyses, and modeling of geological processes. Over his professional experience, Chang Liu has participated in collaborative research projects involving both domestic and international partners, contributing to multi-institutional studies on ore deposit formation and geodynamic fluid systems. His research interest lies particularly in the interplay of pressure–temperature paths, fluid inclusions, and geochemical evolution in gold and other metal deposits, as well as slope stability under hydrological perturbations. In terms of research skills, Chang Liu is proficient in geochemical and petrographic analysis, thermodynamic modeling, structural geology, stable isotope techniques, fluid inclusion microthermometry, and numerical simulation of geological processes. He has published in recognized journals indexed in Scopus, and one of his contributions includes co-authoring a paper on landslide behavior under fluctuating water levels (cited ~25 times) . Chang Liu has been recognized within academic circles, with citations logged in ResearchGate and Scilit, and is steadily gaining visibility through peer collaboration and conference participation. While he has yet to accumulate a large number of awards, his growing citation record and involvement in impactful studies suggest that honors may follow in due course.

Academic Profile: ORCID

Featured Publications:

  1. Liu, C., Coulibaly, Y., Cathelineau, M., & Boiron, M.-C. (2025). Multistage fluid evolution and P–T path at Ity gold deposit and Dahapleu prospect (Western Ivory Coast). Minerals, 15(9).

 

 

Guldane Magat | Dentistry | Best Researcher Award

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Prof. Dr. Guldane Magat | Dentistry | Best Researcher Award

Prof. Dr. Guldane Magat | Dentistry | Professor Doctor at Necmettin Erbakan University Faculty of Dentistry | Turkey

Prof. Dr. Güldane Mağat, a prominent researcher at Necmettin Erbakan Üniversitesi Diş Hekimliği Fakültesi, is recognized for her extensive contributions to dental and maxillofacial radiology, with a particular focus on cone-beam computed tomography (CBCT) applications and craniofacial morphometric analysis. She completed her Ph.D. in Dentistry at Necmettin Erbakan Üniversitesi, gaining comprehensive expertise in advanced imaging techniques, clinical research methodologies, and anatomical assessments. Over the years, Prof. Dr. Güldane Mağat has developed a remarkable professional trajectory, engaging in both national and international research collaborations, leading projects on mandibular and maxillary anatomical studies, and contributing to cross-sectional multinational analyses. Her research interests encompass maxillofacial radiology, trabecular bone pattern evaluation, pulp stone detection, nasopalatine canal morphology, and volumetric analyses of craniofacial structures, reflecting a strong integration of clinical relevance and methodological rigor. Prof. Dr. Güldane Mağat possesses advanced research skills, including 3D volumetric analysis, fractal dimension assessment, gray scale value interpretation, and comparative CBCT and panoramic radiography evaluations, which have enabled her to publish extensively in high-impact journals. She has authored over 30 Scopus-indexed publications, accruing 876 citations, with an h-index of 16 and an i10-index of 21, underscoring her influence in dental imaging research. Her leadership extends beyond research; Prof. Dr. Güldane Mağat has mentored graduate students, guided early-career researchers, and contributed to professional societies and volunteer initiatives, reflecting a commitment to advancing knowledge and supporting the academic community. She has been recognized for her scientific excellence through numerous awards and honors, highlighting her contributions to both research and education. Prof. Dr. Güldane Mağat’s work demonstrates exceptional potential for future advancements in dental imaging, including expanding publications in Q1 journals, increasing participation in international keynote talks, and enhancing global research collaborations.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Gulec, M., Tassoker, M., Magat, G., Lale, B., Ozcan, S., & Orhan, K. (2020). Three-dimensional volumetric analysis of the maxillary sinus: A cone-beam computed tomography study. Folia Morphologica, 79(3), 557–562. (Cited by 81)

  2. Magat, G., & Sener, S. O. (2018). Evaluation of trabecular pattern of mandible using fractal dimension, bone area fraction, and gray scale value: Comparison of cone-beam computed tomography and panoramic radiography. Oral Radiology, 1–8. (Cited by 73)

  3. Tassoker, M., Magat, G., & Sener, S. (2018). A comparative study of cone-beam computed tomography and digital panoramic radiography for detecting pulp stones. Imaging Science in Dentistry, 48(3), 201. (Cited by 61)

  4. Hakbilen, S., & Magat, G. (2018). Evaluation of anatomical and morphological characteristics of the nasopalatine canal in a Turkish population by cone beam computerized tomography. Folia Morphologica. (Cited by 55)

 

 

Firat Yasar | Aerospace | Best Researcher Award

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Dr. Firat Yasar | Aerospace | Best Researcher Award

Dr. Firat Yasar | Aerospace | Scientist at Boeing Research & Technoloy | United States

Dr. Firat Yasar is a highly accomplished scientist at Boeing Research & Technology with expertise in photonics, quantum optics, and microelectronics. He earned his Ph.D. in Physics, focusing on advanced optoelectronic device fabrication and nanophotonic structures, providing him with a strong foundation in both theoretical and applied photonics research. Dr. Firat Yasar has contributed extensively to international research projects, including semiconductor-based systems for atom interferometry experiments in space, and the development of flexible optoelectronic devices with high spatial resolution for X-ray detection. His professional experience spans cutting-edge research in thermal quantum field theory, integrated laser technologies on silicon photonic platforms, and GaN photonic crystals for UV and X-ray applications. Dr. Firat Yasar possesses advanced research skills in nanofabrication, photonic crystal engineering, laser integration, and quantum optics simulation, which have enabled him to deliver innovative solutions in microelectronics and photonics. He has published numerous high-impact articles in reputed journals and conferences, such as IEEE Photonics Journal, Journal of Applied Physics, Optical Fiber Communication Conference, and Journal of the Optical Society of America B, amassing a total of 383 citations with a strong h-index of 6, reflecting the influence and quality of his work. Dr. Firat Yasar has also demonstrated leadership and mentorship by guiding junior researchers, contributing to international collaborations, and actively participating in professional organizations such as IEEE, further enhancing the visibility and impact of his research community contributions. He has received recognition for his innovative work in photonics and optoelectronics, highlighting his ability to combine theoretical insights with practical applications in both industry and academia. Dr. Firat Yasar’s ongoing research interests include flexible amorphous GeSn MSM photodetectors, GaN/InN HEMT-based UV photodetectors, simulation-based design enhancement of multilayer GaN and InN/GaN/AlN photodetectors, and the exploration of quantum speed limits in thermal spin-boson systems.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Khanna, F.C., Malbouisson, A.P.C., Malbouisson, J.M.C., & Santana, A.E. (2009). Thermal quantum field theory: algebraic aspects and applications. World Scientific. (Cited by 275)

  2. Yasar, F., Fan, W., & Ma, Z. (2018). Flexible amorphous GeSn MSM photodetectors. IEEE Photonics Journal, 10(2), 1–9. (Cited by 17)

  3. Yasar, F., Kilin, M., Dehdashti, S., Yu, Z., Ma, Z., & Wang, Z. (2021). Spatially resolved x-ray detection with photonic crystal scintillators. Journal of Applied Physics, 130(4). (Cited by 12)

  4. Yasar, F., Muller, R.E., Khoshakhlagh, A., & Keo, S.A. (2024). Large-area fabrication of nanometer-scale features on GaN using e-beam lithography. Journal of Vacuum Science & Technology B, 42(2). (Cited by 5)

 

Younes Wadiai | Spectroscopy | Best Researcher Award

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Dr. Younes Wadiai | Spectroscopy | Best Researcher Award

Dr. Younes Wadiai | Spectroscopy | Professor at Abdelmalek Essaâdi University | Morocco

Dr. Younes Wadiai is a distinguished Professor of Cybersecurity with extensive expertise in machine learning, deep learning, artificial intelligence, and cybersecurity applications, whose research bridges theoretical innovation with practical solutions for intrusion detection, predictive system modeling, and cloud-based threat mitigation. He earned his Ph.D. in Computer Science and has consistently contributed to advancing cybersecurity and AI-driven solutions through active participation in international collaborative projects. Dr. Younes Wadiai has been instrumental in leading research initiatives at the TIAD Laboratory, Sultan Moulay Slimane University, Morocco, focusing on intelligent system design for stability assessment, real-time threat detection, and automation of cybersecurity processes. His professional experience spans multiple interdisciplinary projects that integrate AI and cybersecurity methodologies to enhance system resilience and operational efficiency. Dr. Younes Wadiai’s research interests include developing generative adversarial network (GAN) models to address data scarcity, designing decision-support systems for information system attacks, and creating predictive analytics tools for industrial and healthcare applications. He has demonstrated significant research skills in designing machine learning architectures, implementing neural network-based intrusion detection systems, and leveraging semi-supervised learning approaches for real-world datasets. Dr. Younes Wadiai has authored and co-authored multiple publications in reputed journals and conferences such as the International Journal of Advanced Computer Science and Applications, Journal of Theoretical and Applied Information Technology, and IEEE-aligned conferences, reflecting his growing scholarly impact with a total of 27 citations, h-index of 2, and i10-index of 1. He is actively engaged in mentoring students, organizing international conferences, and fostering cross-institutional research collaborations. His leadership and contributions to the academic community are further strengthened by his involvement in professional networks and memberships in recognized technical societies.

Academic Profile: Scopus | Google Scholar

Featured Publications:

  1. El Mourabit, Y., El Habouz, Y., Zougagh, H., & Wadiai, Y. (2020). Predictive system of semiconductor failures based on machine learning approach. International Journal of Advanced Computer Science and Applications. Citations: 18

  2. Wadiai, Y., & Baslam, M. (2022). Machine learning approach to automate decision support on information system attacks. International Conference on Business Intelligence, 71–81. Citations: 2

  3. Wadiai, Y., El Mourabit, Y., & Baslam, M. (2020). Machine learning for intrusion detection: Design and implementation of an IDS based on artificial neural network. International Conference on Innovations in Bio-Inspired Computing. Citations: 2

  4. Wadiai, Y., El Mourabit, Y., Baslam, M., & Nassiri, B. (2023). Real-time cloud-based automation for cyber threats detection and mitigation with machine learning models. Journal of Theoretical and Applied Information Technology, 101(22).

 

 

Zhilan Ke | Geropsychology | Best Researcher Award

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Ms. Zhilan Ke | Geropsychology | Best Researcher Award

Ms. Zhilan Ke | Geropsychology | Hubei University of Chinese Medicine | China

Ms. Zhilan Ke, a dedicated researcher from Hubei University of Chinese Medicine in Wuhan, China, is steadily emerging as a promising scholar in the domain of health sciences with a particular emphasis on digital health interventions and gerontology. Ms. Zhilan Ke completed her advanced academic training at Hubei University of Chinese Medicine, where she pursued doctoral-level studies with strong emphasis on applied health sciences and clinical research methodology, giving her a firm foundation for research involving both traditional medicine approaches and modern digital technologies. Throughout her academic journey, Ms. Zhilan Ke has demonstrated a strong interest in harnessing the potential of technology to address contemporary challenges in healthcare, particularly those related to the psychological well-being of aging populations. In terms of professional experience, Ms. Zhilan Ke has been actively involved in conducting systematic reviews and meta-analyses with international research teams, bringing together evidence across multiple randomized controlled trials to evaluate the effectiveness of innovative healthcare solutions. Her most recognized contribution so far is her study on the impact of immersive virtual reality in improving the mental health and quality of life of older adults, a publication indexed in Scopus that has gained early recognition with 3 citations from 3 documents, 1 indexed publication, and an h-index of 1, indicating both the relevance and potential of her work to guide policy and future studies in this area. Her research interests cover a wide spectrum, including digital health, virtual reality therapy, geriatric care, evidence-based medicine, and cross-disciplinary collaborations that integrate psychology, public health, and biomedical informatics. Within her skillset, Ms. Zhilan Ke is proficient in systematic review methodology, statistical meta-analysis, and the application of rigorous evidence synthesis to derive meaningful healthcare recommendations, along with competencies in collaborative research and academic writing for internationally recognized journals. In addition to her academic and technical skills, Ms. Zhilan Ke demonstrates strong professional values by contributing to the global research community through co-authorship networks, mentoring young students, and taking part in knowledge-sharing initiatives. Although still early in her career, Ms. Zhilan Ke has already begun to receive recognition for her innovative approach, as reflected in her indexed publications, measurable research impact, and growing visibility through international citations. Her emerging record positions her as a future leader in the integration of digital technology into healthcare for vulnerable populations.

Academic Profile: Scopus

Featured Publications:

Ke, Z. (n.d.). The effectiveness of immersive virtual reality on the psychology of older adults: A systematic review and meta-analysis of randomized controlled trials. [Published 2025, 3 citations].

 

 

Mai Abd El Meguid | Virology | Best Researcher Award

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Assoc. Prof. Dr. Mai Abd El Meguid | Virology | Best Researcher Award

Assoc. Prof. Dr. Mai Abd El Meguid | Virology | Associated Professor at National Research Centre | Egypt

Assoc. Prof. Dr. Mai Abd El Meguid is a distinguished molecular biologist at the National Research Centre, recognized for her outstanding contributions to liver disease, viral hepatitis, and cancer genetics research. She earned her Ph.D. in Molecular Biology from a leading university and has since developed an extensive professional experience portfolio, including leading multiple national and international research projects. Her research interests focus on hepatic fibrosis, hepatitis C virus pathogenesis, cytomegalovirus reactivation, and the impact of direct-acting antivirals on liver function, with an emphasis on translational applications that inform clinical interventions. Dr. Mai Abd El Meguid possesses strong research skills in molecular biology techniques, bioinformatics, gene expression analysis, and clinical data interpretation, enabling her to design and execute high-impact studies with precision. Her academic leadership is demonstrated through mentoring graduate students, guiding research teams, and contributing to professional organizations and volunteer platforms. She has an impressive publication record, with over 320 citations, an h-index of 10, and numerous contributions to high-impact journals such as Journal of Interferon & Cytokine Research, Genes & Diseases, and The American Journal of the Medical Sciences. Dr. Mai Abd El Meguid has received multiple awards and honors recognizing her research excellence, including acknowledgment from professional societies and academic institutions for her innovative contributions to liver disease research and public health impact. Her work has significantly advanced understanding of molecular mechanisms underlying liver fibrosis and viral hepatitis, as well as provided insights into personalized medical approaches for patients with chronic hepatitis C. With a combination of research expertise, leadership experience, and a record of scholarly excellence, Dr. Mai Abd El Meguid demonstrates remarkable potential for future contributions to biomedical research, particularly in enhancing Q1 journal publications, expanding global collaborations, and participating in international keynote lectures. Her career trajectory reflects a consistent commitment to scientific rigor, mentorship, and translating research outcomes into societal benefit. In conclusion, Dr. Mai Abd El Meguid is a highly deserving candidate for research awards and recognitions due to her significant scientific contributions, leadership in the field, and potential to drive impactful, globally relevant research in molecular biology and liver disease for years to come.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Dawood, R. M., El-Meguid, M. A., Salum, G. M., & El Awady, M. K. (2020). Key players of hepatic fibrosis. Journal of Interferon & Cytokine Research, 40(10), 472–489. Cited by 66

  2. Dawood, R. M., Salum, G. M., El-Meguid, M. A. (2022). The impact of COVID-19 on liver injury. The American Journal of the Medical Sciences, 363(2), 94–103. Cited by 62

  3. Salum, G. M., Dawood, R. M., El-Meguid, M. A., Ibrahim, N. E., Aziz, A. O. A., … (2020). Correlation between IL28B/TLR4 genetic variants and HCC development with/without DAAs treatment in chronic HCV patients. Genes & Diseases, 7(3), 392–400. Cited by 32

  4. Bader El Din, N. G., El-Meguid, M. A., Tabll, A. A., Anany, M. A., Esmat, G., … (2011). Human cytomegalovirus infection inhibits response of chronic hepatitis‐C‐virus‐infected patients to interferon‐based therapy. Journal of Gastroenterology and Hepatology, 26(1), 55–62. Cited by 32

 

 

Xin Tong | Control | Best Researcher Award

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Prof. Xin Tong | Control | Best Researcher Award

Prof. Xin Tong | Control | Associate professor at Northeastern University | China

Prof. Xin Tong is an accomplished Associate Professor at the School of Business Administration, Northeastern University, Shenyang, China, with a distinguished career in the study of digital economy, green development, and sustainable management practices. Prof. Xin Tong obtained a Ph.D. in management from a reputed university, which laid a strong foundation for her interdisciplinary research in economic development, policy-driven sustainability, and technological innovation. Over the course of her professional career, Prof. Xin Tong has participated in several significant research projects, including international collaborations that examine the mechanisms of digital transformation and its environmental and economic impacts. Her research interests focus on digital economy frameworks, green development strategies, spillover effects of policy interventions, and the transmission mechanisms that drive sustainable economic growth. Prof. Xin Tong has demonstrated exceptional research skills in quantitative modeling, econometric analysis, and interdisciplinary policy evaluation, which have enabled her to publish in high-impact journals indexed in Scopus and Web of Science. Notably, her work has contributed to the understanding of how digital technologies influence environmental sustainability and economic development. Prof. Xin Tong has also actively taken on leadership roles, mentoring graduate students, coordinating research initiatives, and participating in professional organizations to promote academic excellence and knowledge dissemination. She has received recognition and awards for her contributions to research and teaching, highlighting her commitment to advancing the field of business administration and sustainable development.

Academic Profile: ORCID

Featured Publications:

  1. Tong, X., Li, K., & Li, X. (2025). Digital Economy and Green Development: Mechanisms of Action, Spillover Effects and Transmission Mechanisms. Entropy, 27(9), 966. Citations: 1

 

 

Somayeh Najafi-Ghobadi | Econometrics | Best Researcher Award

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Assist. Prof. Dr. Somayeh Najafi-Ghobadi | Econometrics | Best Researcher Award

Assist. Prof. Dr. Somayeh Najafi-Ghobadi | Econometrics | Assistant profesor at Kermanshah university of technology | Iran

Assist. Prof. Dr. Somayeh Najafi-Ghobadi is a dedicated academic and researcher whose scholarly work integrates industrial engineering, operations research, data mining, and healthcare analytics, making her a highly recognized contributor in multidisciplinary research environments. She obtained her Ph.D. in Industrial Engineering and currently serves as an Assistant Professor in the Department of Industrial Engineering at Kermanshah University of Technology, where she actively mentors students, leads research initiatives, and contributes to institutional academic excellence. Her professional experience includes extensive involvement in research projects focusing on optimization, supply chain management, and data-driven modeling, as well as collaborations with prominent scholars from institutions such as the University of Tehran, Alzahra University, and Tecnológico de Monterrey, which highlight her ability to work in international and cross-disciplinary teams. Assist. Prof. Dr. Somayeh Najafi-Ghobadi has cultivated expertise in game theory, machine learning applications, and predictive modeling, contributing to both theoretical advancements and real-world problem-solving, particularly in industrial decision-making and healthcare applications. Her research interests cover a wide range of interconnected domains, including closed-loop supply chains, new product diffusion modeling, dynamic pricing, healthcare informatics, and predictive analytics for patient outcomes. With a citation count of over 136, an h-index of 7, and an i10-index of 6, her publications in high-quality journals indexed in Scopus and IEEE demonstrate not only the visibility but also the impact of her research contributions. She has published influential works on subjects such as pricing and supplier selection in closed-loop supply chains, machine learning classifiers for predicting low birth weight, and optimization of marketing-mix strategies for new generation products, which reflect her versatility and problem-oriented approach to complex challenges. In terms of research skills, Assist. Prof. Dr. Somayeh Najafi-Ghobadi is proficient in advanced mathematical modeling, algorithm development, data mining, and statistical analysis, and she applies these skills to both industrial optimization problems and health-related predictive studies.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

Najafi-Ghobadi, S., & Esmaeili, M. (2018). A game theory model for pricing and supplier selection in a closed-loop supply chain. International Journal of Procurement Management, 11(4), 472–494. Citations: 25

Arayeshgari, M., Najafi-Ghobadi, S., Tarhsaz, H., Parami, S., & Tapak, L. (2023). Machine learning-based classifiers for the prediction of low birth weight. Healthcare Informatics Research, 29(1), 54–63. Citations: 19

Najafi-Ghobadi, S., Bagherinejad, J., & Taleizadeh, A. A. (2021). A two-generation new product model by considering forward-looking customers: Dynamic pricing and advertising optimization. Journal of Retailing and Consumer Services, 63, 102387. Citations: 19

Najafi-Ghobadi, S., Bagherinejad, J., & Taleizadeh, A. A. (2021). Modeling the diffusion of generation products in the presence of heterogeneous strategic customers for determining optimal marketing-mix strategies. Computers & Industrial Engineering, 160, 107606. Citations: 16

 

Bo Zhang | Environmental Science | Best Research Article Award

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Mr. Bo Zhang | Environmental Science | Best Research Article Award

Mr. Bo Zhang | Environmental Science | Associate Professor at Northwestern Polytechnical University | China

Mr. Bo Zhang is an accomplished researcher whose career reflects a distinguished trajectory in the fields of remote sensing, geoinformation science, and artificial intelligence applications for environmental monitoring, and he has consistently demonstrated excellence through impactful research contributions and global collaborations. Educated with a doctoral degree in Remote Sensing from a leading academic institution, Mr. Bo Zhang has established a solid academic foundation that underpins his expertise in applying advanced computational methods to real-world environmental challenges. His professional experience includes multiple collaborative projects with internationally recognized scholars from institutions such as Tsinghua University, Southeast University, Technical University of Munich, University of Hong Kong, and others, through which he has advanced the use of deep learning techniques, satellite image downscaling, and GIS-based data integration for earth observation and climate-related studies. Mr. Bo Zhang’s research interests lie primarily in satellite remote sensing, super-resolution reconstruction of geospatial datasets, atmospheric and environmental data analysis, epidemiological mapping, and the integration of machine learning for improved predictive accuracy in public health and ecological monitoring, reflecting an interdisciplinary approach that combines computing, earth science, and applied technology. His research skills span deep learning model development, neural network applications for image processing, spatial epidemiology analysis, super-resolution algorithms, and the integration of volunteered geographic information into traditional mapping platforms, enabling him to contribute both theoretically and practically to geospatial sciences.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  • Zhu, B., Liu, J., Fu, Y., Zhang, B., & Mao, Y. (2018). Spatio-temporal epidemiology of viral hepatitis in China (2003–2015): Implications for prevention and control policies. International Journal of Environmental Research and Public Health, 15(4), 661. Citations: 73.

  • Pan, D., Zhang, M., & Zhang, B. (2021). A generic FCN-based approach for the road-network extraction from VHR remote sensing images—Using OpenStreetMap as benchmarks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. Citations: 59.

  • Zhang, B., Zhang, M., Kang, J., Hong, D., Xu, J., & Zhu, X. (2019). Estimation of PMx concentrations from Landsat 8 OLI images based on a multilayer perceptron neural network. Remote Sensing, 11(6), 646. Citations: 29.

  • Zhang, B., Xiong, W., Ma, M., Wang, M., Wang, D., Huang, X., Yu, L., Zhang, Q., … (2022). Super-resolution reconstruction of a 3 arc-second global DEM dataset. Science Bulletin, 67(24), 2526–2530. Citations: 25.

 

 

Henry Ogbu | Artificial Intelligence | Best Researcher Award

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Mr. Henry Ogbu | Artificial Intelligence | Best Researcher Award

Mr. Henry Ogbu | Artificial Intelligence | Assistant Lecturer at Covenant University | Nigeria

Mr Henry Ogbu is an emerging scholar and researcher in the field of Computer and Information Science whose academic journey and professional achievements demonstrate a strong commitment to advancing artificial intelligence and computational intelligence. He pursued his higher education at Covenant University, Nigeria, where he specialized in Computer and Information Science, acquiring a solid academic foundation that enabled him to explore machine learning, optimization algorithms, and recommender systems in depth. Through his education and research training, Mr Henry Ogbu developed expertise in algorithm design, neural network optimization, and intelligent systems modeling, positioning himself as a promising academic with innovative contributions to technology-driven solutions. Professionally, Mr Henry Ogbu has participated actively in research projects, presenting his work at international conferences and publishing in peer-reviewed journals and conference proceedings indexed in Scopus and IEEE databases. His professional experience reflects a dedication to solving practical problems through artificial intelligence applications, including automated grading systems, operating system evaluation, and optimization strategies in computational models. His research interests cover deep learning, neural networks, optimization techniques, artificial intelligence, and intelligent recommender systems, with an emphasis on designing models that are efficient, scalable, and adaptable to modern computational challenges. In his published works, such as iAttention Transformer: An Inter-Sentence Attention Mechanism for Automated Grading and Application of Optimization Techniques in Recommender Systems, he demonstrates both technical rigor and practical applicability, thereby contributing to the global body of knowledge in artificial intelligence. His skills extend across several domains including advanced algorithm development, optimization modeling, neural network training, data-driven analysis, and collaborative research across interdisciplinary domains. Mr Henry Ogbu is adept in employing mathematical foundations, coding skills, and machine learning frameworks to design and evaluate systems, making his research highly relevant to academia and industry. Alongside his research expertise, he has also participated in academic leadership roles, contributing to collaborative projects and engaging with the broader research community through conference presentations and knowledge-sharing forums.

Academic Profile: ORCID | Google Scholar

Featured Publications:

Ogbu, H. N., Dada, I. D., Akinwale, A. T., Osinuga, I. A., & Tunde-Adeleke, T. J. (2025). iAttention Transformer: An inter-sentence attention mechanism for automated grading. Mathematics, 13(18), 2991.

Ogbu, H. N. (2024). Application of optimization techniques in recommender systems. Proceedings of the International Conference on Computer Science.

Ogbu, H. N. (2024). Training neural network model using an improved three-term conjugate gradient algorithm. In Proceedings of the 1st International Conference & Research Showcase on Science, Technology & Innovation (ICRS-STI 2024).

Ogbu, H. N. (2021). Comparative study of operating system quality attributes. IOP Conference Series: Materials Science and Engineering, 1107(1), 012061. — Citations: 6