Razi Al-Azawi | Image Processing | Research Excellence Award

Published on by Research Data Analysis

Prof. Dr. Razi Al-Azawi | Image Processing | Research Excellence Award

University of Technology | Iraq

Prof. Dr. Razi Al-Azawi is a distinguished academic and researcher specializing in informatics, artificial intelligence, and advanced computational systems. He holds dual B.Sc. degrees in Laser and Optoelectronics Engineering from the University of Technology and Mathematical Sciences from Mustansiriah University, an M.Sc. in Modeling and Simulation from the University of Technology, and a PhD in Informatics from Kharkov National University of Radio Electronics. Over a career spanning more than two decades, he has taught a wide range of postgraduate and undergraduate courses, including image processing, deep learning, AI, modeling and simulation, information theory, optimization, probability, web design, and advanced programming. His research interests encompass machine learning, data mining, medical image analysis, laser engineering, cybersecurity, and advanced computational modeling. He has supervised over 50 undergraduate theses and numerous postgraduate dissertations at the Higher Diploma, M.Sc., and PhD levels. His scholarly output includes 16 documents, 264 citations by 257 documents, and an h-index of 6. He has served as a reviewer for several international journals and conferences and holds multiple patents under processing. Through his academic leadership and scientific contributions, he continues to advance innovation in computer science, AI, and engineering domains.

Profiles : Scopus |

Featured Publications

Samaneh Saeedinia | Engineering | Best Researcher Award

Published on by Research Data Analysis

Prof.Dr. Samaneh Saeedinia | Engineering | Best Researcher Award

Iran University of Science and Technology | Iran

Dr. Samaneh Alsadat Saeedinia is an accomplished researcher and engineer specializing in Control Electrical Engineering, Computational Neuroscience, Robotics, and Artificial Intelligence. She earned her Ph.D. from Iran University of Science and Technology (IUST), where her thesis focused on designing and stabilizing intelligent decision-making systems to support the treatment of adult focal epilepsy, receiving an excellent grade. She also holds a Master’s degree in Control Electrical Engineering from IUST and a Bachelor’s degree from Imam Khomeini International University. Dr. Saeedinia has extensive experience in signal processing, machine learning, spiking neural networks, EEG and MRI data analysis, and adaptive control systems. She has contributed to numerous high-impact publications in IEEE Transactions, Scientific Reports, and other international journals. Her research interests include computational modeling, intelligent control, data fusion, robotics path planning, and neuroinformatics. Beyond academia, she has led industrial projects in electrical power systems, automation, and instrumentation. She has received multiple awards, including the Khwarizmi International Award and top ranks in academic performance. Dr. Saeedinia is also an experienced educator and mentor, guiding students in advanced control systems, neural networks, and data analysis. Her work bridges engineering, neuroscience, and artificial intelligence, aiming to develop innovative solutions for healthcare and robotic applications.

Profile : Google Scholar

Featured Publications

Saeedinia, S.A., Jahed-Motlagh, M.R., Tafakhori, A., & Kasabov, N.K. (2024). “Diagnostic biomarker discovery from brain EEG data using LSTM, reservoir-SNN, and NeuCube methods in a pilot study comparing epilepsy and migraine” in Scientific Reports, 14(1), 10667.

Mohaghegh, M., Saeedinia, S.A., & Roozbehi, Z. (2023). “Optimal predictive neuro-navigator design for mobile robot navigation with moving obstacles” in Frontiers in Robotics and AI, 10, 1226028.

Roozbehi, Z., Narayanan, A., Mohaghegh, M., & Saeedinia, S.A. (2024). “Dynamic-structured reservoir spiking neural network in sound localization” in IEEE Access, 12, 24596–24608.

Saeedinia, S.A., & Tale Masouleh, M. (2022). “The synergy of the multi-modal MPC and Q-learning approach for the navigation of a three-wheeled omnidirectional robot based on the dynamic model with obstacle collision” in Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.

Roozbehi, Z., Narayanan, A., Mohaghegh, M., & Saeedinia, S.A. (2025). “Enhanced Multiple Sound Event Detection and Classification Using Physical Signal Properties in Recurrent Spiking Neural Networks” in IEEE Access.

Mohammad Zeyauddin | Qualitative Research | Best Researcher Award

Published on by Research Data Analysis

Assist. Prof. Dr. Mohammad Zeyauddin | Qualitative Research | Best Researcher Award

Jubail Industrial College | Saudi Arabia

Dr. Mohammad Zeyauddin is an accomplished Assistant Professor in the Department of General Studies, Mathematics Section, at Jubail Industrial College, Saudi Arabia. With over fourteen years of teaching experience at undergraduate and postgraduate levels, he has contributed significantly to curriculum development, academic mentorship, and student engagement. Dr. Zeyauddin holds a Ph.D. in Applied Mathematics from Banaras Hindu University, India, with research focused on spatially homogeneous and anisotropic Bianchi Type V cosmological models in general relativity and scalar-tensor theories of gravitation. He also completed a Post-Doctoral Fellowship at the Joint Institute for Nuclear Research, Dubna, Russia, specializing in relativistic cosmology. His teaching repertoire spans Linear Algebra, Differential and Integral Calculus, Differential Equations, Complex and Functional Analysis, Tensor Analysis, Probability and Statistics, and Computational Mathematics. He has published over 30 international research papers and serves as a reviewer for the American Mathematical Society. His research interests include non-linear differential equations, general relativity, cosmology, and scalar-tensor theories of gravitation. Recognized for academic excellence, he has received UGC Junior and Senior Research Fellowships, postdoctoral fellowships, and appreciation for curriculum contributions. Dr. Zeyauddin continues to inspire students and peers through innovative teaching, research, and contributions to mathematical sciences.

Profile : Orcid

Featured Publications

Dayanandan, B., Pradhan, A., Zeyauddin, M., & Banerjee, A. (2025). Quark stars with strongly interacting quark matter in energy-momentum squared gravity. International Journal of Geometric Methods in Modern Physics.

Pradhan, A., Zeyauddin, M., Dixit, A., & Krishnannair, S. (2025). Dust-fluid accelerating flat cosmological models in f(R,T,Lm)-gravity with observational constraints. International Journal of Geometric Methods in Modern Physics.

Pradhan, A., Zeyauddin, M., Dixit, A., & Ghaderi, K. (2025). Phantom dark energy behavior in Weyl type f(Q,T) gravity models with observational constraints. Universe, 11(8).

Pradhan, A., Dayanandan, B., Zeyauddin, M., & Banerjee, A. (2025). On the possible existence of wormholes in Rastall–Rainbow gravity. International Journal of Modern Physics A.

Pradhan, A., Dixit, A., Zeyauddin, M., & Krishnannair, S. (2024). A flat FLRW dark energy model in f(Q,C)-gravity theory with observational constraints. International Journal of Geometric Methods in Modern Physics.

Ying Jin | Big Data Analytics | Best Researcher Awards

Published on by Research Data Analysis

Ying Jin | Big Data Analytics | Best Researcher Award

Professor, Nanjing University, China

Profile

 Scopus 

Prof. Jin Ying is a Professor at the Department of Computer Science and Technology, Nanjing University, widely recognized for her leadership and contributions in computer education, data mining, citation analysis, big data, and virtual reality applications. Her career bridges teaching, research, and academic service, reflecting a strong commitment to advancing both theoretical knowledge and practical innovations in the field of computer science. She has served in multiple influential academic and professional roles, helping shape the direction of education and technology integration in China.

Education

Prof. Jin began her academic journey in geochemistry and later transitioned into information management and computer science, bringing an interdisciplinary perspective to her work. She earned her Ph.D. in Management with a specialization in data mining and CSSCI research, which laid the foundation for her impactful contributions in citation analysis, big data, and education technology. Her diverse educational background allows her to integrate cross-disciplinary insights into computer science education and applied research.

Experience

Throughout her career at Nanjing University, Prof. Jin has advanced from teaching assistant to lecturer, associate professor, and eventually full professor. She teaches a wide range of courses including computer applications, Visual Basic, Python, and C programming, with her pedagogy focusing on innovation and practical engagement. Beyond the classroom, she serves as Group Lead of Visual Basic and Secretary of the Center of College Computer Test in Jiangsu Province. She is also an active member of the Computer Education Supervisory Committee (MOE, Liberal Arts), Jiangsu Computer Foundation Education Committee, and the Council on East China University Computer Foundation Education. Additionally, she contributes as a judge for the National College Computer Design Competition and as a peer reviewer for CSSCI-indexed journals.

Research Interests

Prof. Jin’s research integrates education and technology, addressing critical issues such as AI-driven talent training models, programming pedagogy reform in the AI era, flipped classroom strategies, big data course design for non-computer majors, and innovations in youth IT education. She has published widely in international journals and conferences, making significant contributions to the fields of data mining, education reform, and computational thinking. Her authored teaching resources, including College Basic Computer Applications and New Visual Basic Programming, are used across universities and contribute to improving computer education nationwide.

Awards

Prof. Jin’s achievements have been recognized through numerous awards and honors. She received the prestigious First Tan Haoqiang Computer Education Fund Outstanding Teacher Award and Nanjing University’s Shilin Teaching Award, reflecting her excellence in teaching and mentorship. She has also earned multiple best paper awards and nominations at international conferences, alongside prizes for guiding student projects in national-level computer design competitions. These recognitions highlight her dual impact as both a researcher and educator.

Featured Publications

  • Jin, Y. (2024). Exploration of K12 Multi-level Information and AI Talent Training Model.

  • Jin, Y. (2024). Exploration on Teaching Content Reform of Programming Course in the Era of AI.

  • Jin, Y. (2024). A survey of research on several problems in the RoboCup3D simulation environment.

  • Jin, Y. (2023). The Role of Science and Technology Innovation Competition in Talent Cultivation and Development.

  • Jin, Y. (2022). An approach for evaluating course acceptance based on Bayesian network. Int. J. of Intelligent Internet of Things Computing.

  • Jin, Y. (2022). Design and Implementation of a Cloud-Native Platform for Financial Big Data Processing Course.

  • Jin, Y. (2022). Hierarchical and Diverse Cultivation of Data Thinking Capability in College Based on New High School Curriculum Standards.

Conclusion

By combining rigorous scholarship, innovative teaching, and impactful leadership, Prof. Jin Ying has significantly advanced computer education reform and promoted the integration of technology with pedagogy. Her interdisciplinary vision and ability to merge data-driven methods with educational practice have influenced generations of students, equipping them with computational skills essential for the digital age. Through her roles in research, teaching, academic committees, and national projects, she continues to shape the landscape of computer science education in China and beyond, fostering a forward-looking environment that bridges research, practice, and innovation.