Muhammad Qiyas | Mathematics | Best Researcher Award

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Assist. Prof. Dr. Muhammad Qiyas | Mathematics | Best Researcher Award

Assistant Professor at Riphah International University Faisalabad, Pakistan

Muhammad Qiyas is an accomplished academic and researcher in the field of mathematics, specializing in fuzzy decision-making, aggregation operators, and multi-criteria decision analysis. With a strong passion for problem-solving and knowledge dissemination, he has contributed significantly to academia through teaching, research, and publishing in high-impact journals. His career spans various educational institutions, where he has played a pivotal role in mentoring students, supervising research projects, and advancing mathematical research. His dedication to continuous learning and interdisciplinary collaboration has established him as a leading expert in his domain.

Profile

Scopus

Education

Muhammad Qiyas holds a Ph.D. in Mathematics from Abdul Wali Khan University Mardan, Pakistan, completed in 2020. His doctoral research focused on “Aggregation Operators on Linguistic Picture Fuzzy Sets and their Applications in Decision Making Problems,” showcasing his expertise in mathematical modeling and decision science. Prior to that, he obtained an MS in Mathematics from Mohi-Ud-Din Islamic University, Islamabad, Pakistan, where he explored the domain of Orthodox Γ-Semigroup. He completed his Bachelor’s in Mathematics from the University of Malakand, KP, Pakistan, with a project on “Rule of Prime Numbers in Cryptography,” demonstrating his early interest in computational mathematics.

Professional Experience

Muhammad Qiyas is currently serving as an Assistant Professor at Riphah International University Faisalabad Campus, Pakistan. In this role, he is responsible for delivering high-quality instruction in mathematics, supervising graduate research projects, and contributing to the university’s research output. Additionally, he holds a Research Fellow position at Universiti Sultan Zainal Abidin, Malaysia, where he collaborates on cutting-edge research in mathematical decision-making. His previous experience includes active participation in international conferences, editorial responsibilities in academic journals, and contributions to mathematical research communities worldwide.

Research Interests

Muhammad Qiyas specializes in fuzzy set theory, aggregation operators, decision-making models, and multi-criteria decision analysis. His research primarily focuses on developing novel mathematical techniques to enhance decision support systems. His work on picture fuzzy sets, spherical fuzzy aggregation, and hybrid decision-making models has significantly contributed to advancing computational intelligence and applied mathematics. He actively explores new approaches to uncertainty modeling and their applications in various real-world problems, including supply chain management, engineering decision-making, and artificial intelligence.

Awards and Recognitions

Muhammad Qiyas has been recognized for his contributions to mathematical research and education. His work has been cited in numerous high-impact journals, showcasing the influence of his research on the global academic community. He has also been invited as a speaker at prestigious mathematics conferences, demonstrating his expertise and thought leadership in fuzzy decision-making and aggregation operators. His scholarly achievements have earned him nominations for awards in academia and research excellence.

Publications

Zeng, S., Qiyas, M., Arif, M., & Mahmood, T. (2019). Extended version of linguistic picture fuzzy TOPSIS method and its applications in enterprise resource planning systems. Mathematical Problems in Engineering.

Qiyas, M., Abdullah, S., Ashraf, S., & Abdullah, L. (2019). Linguistic picture fuzzy Dombi aggregation operators and their application in multiple attribute group decision-making problems. Mathematics, 7(8), 764.

Khan, A.A., Ashraf, S., Abdullah, S., Qiyas, M., Luo, J., & Khan, S.U. (2019). Pythagorean fuzzy Dombi aggregation operators and their application in decision support systems. Symmetry, 11(3), 383.

Khan, A.A., Qiyas, M., Abdullah, S., Luo, J., & Bano, M. (2019). Analysis of robot selection based on 2-tuple picture fuzzy linguistic aggregation operators. Mathematics, 7(10), 1000.

Jin, H., Ashraf, S., Abdullah, S., Qiyas, M., Bano, M., & Zeng, S. (2019). Linguistic spherical fuzzy aggregation operators and their applications in multi-attribute decision-making problems. Mathematics, 7(5), 413.

Ashraf, S., Abdullah, S., Aslam, M., Qiyas, M., & Kutbi, M.A. (2019). Spherical fuzzy sets and its representation of spherical fuzzy t-norms and t-conorms. Journal of Intelligent & Fuzzy Systems, 36(6), 6089-6102.

Ashraf, S., Abdullah, S., Qiyas, M., & Khan, A. (2019). Picture fuzzy grey approach for decision problems with unknown weight information. Journal of Biostatistics and Biometric Applications, 4(1).

Conclusion

Muhammad Qiyas has made significant contributions to the field of mathematics through his research, teaching, and publications. His work in fuzzy set theory and decision-making models has provided valuable insights into complex mathematical and computational problems. With a strong academic background, extensive research experience, and a commitment to advancing mathematical sciences, he continues to influence the field through innovation and collaboration. His future endeavors will likely further enhance the application of mathematical methodologies in decision science and computational intelligence.

Zhigang Jia | Mathematics | Best Researcher Award

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Prof. Zhigang Jia | Mathematics | Best Researcher Award

Professor at Jiangsu Normal University, China

Zhigang Jia is a distinguished professor and researcher in the field of numerical mathematics and image processing. With an extensive academic career spanning over a decade, he has contributed significantly to mathematical sciences, particularly in matrix computations and image recognition. Currently serving as a professor at Jiangsu Normal University, he has also been affiliated with renowned institutions such as the University of Macau and Hong Kong Baptist University. His research primarily focuses on numerical algorithms, low-rank approximation, and their applications in medical imaging and artificial intelligence. Through his work, he has established himself as a leading scholar in computational mathematics.

Profile

Orcid

Education

Zhigang Jia pursued his PhD in Mathematics at East China Normal University under the supervision of Prof. Musheng Wei from 2006 to 2009. Prior to that, he earned his Master’s degree from Liaocheng University in 2006, guided by Prof. Jianli Zhao. His academic journey began with a Bachelor’s degree in Mathematics from Liaocheng University, which he completed in 2003. His rigorous training in mathematical sciences laid the foundation for his research in numerical algorithms, computational science, and image processing techniques.

Experience

Zhigang Jia has held multiple academic and research positions throughout his career. He began as a Lecturer at Jiangsu Normal University in 2009 and was subsequently promoted to Associate Professor in 2011. In 2014, he was appointed as a Professor at Jiangsu Normal University, where he continues to lead research in numerical mathematics and image processing. He has also served as a researcher at Jiangsu Key Laboratory of Education Big Data Science and Engineering and the Research Institute of Mathematical Science. Additionally, he has undertaken international academic visits, including a postdoctoral research tenure at Hong Kong Baptist University (2018–2019) and a visiting scholar role at the University of Macau (2019). His experience reflects his dedication to advancing mathematical sciences globally.

Research Interests

Zhigang Jia’s research focuses on numerical mathematics, image processing, and face recognition. His work extensively explores low-rank approximation problems, structure-preserving algorithms, and large-scale matrix computations. His research has been applied in various fields, including medical imaging, artificial intelligence, and digital watermarking. He is particularly interested in quaternion matrix computations and their application in color image restoration and video inpainting. His contributions to structural matrix polynomials and spectral decomposition have enhanced the computational efficiency of large-scale data processing.

Awards

Throughout his career, Zhigang Jia has been recognized for his contributions to numerical mathematics and image processing. He has received multiple research grants from the National Science Foundation of China, where he served as the Principal Investigator for projects focusing on data-driven low-rank approximation and structural matrix polynomials. His innovative work in computational mathematics has earned him accolades from academic institutions and research bodies, highlighting his impact on mathematical sciences and engineering applications.

Publications

Zhigang Jia, Yuelian Xiang, Meixiang Zhao, Tingting Wu, and Michael K. Ng, “A new cross-space total variation regularization model for color image restoration with quaternion blur operator,” IEEE Transactions on Image Processing, 34, 995-1008, 2025.

Baohua Huang, Zhigang Jia, and Wen Li, “A Novel Riemannian Conjugate Gradient Method on Quaternion Stiefel Manifold for Computing Truncated Quaternion Singular Value Decomposition,” Numerical Linear Algebra with Applications, 32(1), e70006, 2025.

Yong Chen, Zhigang Jia, Yaxin Peng, and Yan Peng, “Efficient Robust Watermarking Based on Structure-Preserving Quaternion Singular Value Decomposition,” IEEE Transactions on Image Processing, 32, 3964-3979, 2023.

Zhigang Jia, Qianyu Wang, Hongkui Pang, and Meixiang Zhao, “Computing partial quaternion eigenpairs with quaternion shift,” Journal of Scientific Computing, 97, article number 41, 2023.

Zhigang Jia, Qiyu Jin, Michael K. Ng, and Xi-Le Zhao, “Non-local robust quaternion matrix completion for large-scale color image and video Inpainting,” IEEE Transactions on Image Processing, 31, 3868-3883, 2022.

Qiaohua Liu, Sitao Ling, and Zhigang Jia, “Randomized quaternion singular value decomposition for low-rank matrix approximation,” SIAM Journal on Scientific Computing, 44(2), A870-A900, 2022.

Qiaohua Liu, Zhigang Jia, and Yimin Wei, “Multidimensional total least squares problem with linear equality constraints,” SIAM Journal on Matrix Analysis and Applications, 43(1), 124–150, 2022.

Conclusion

Zhigang Jia’s extensive contributions to numerical mathematics, image processing, and computational science have solidified his reputation as a leading researcher. His work in quaternion matrix computations and low-rank approximation methods has influenced multiple disciplines, including artificial intelligence and medical imaging. With numerous high-impact publications, prestigious research grants, and international collaborations, he continues to advance mathematical sciences and its applications. His dedication to research and innovation ensures that his work will have a lasting impact on computational mathematics and beyond.

Alaa Aldeen Joumah | Bayesian Inference | Best Researcher Award

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Mr. Alaa Aldeen Joumah | Bayesian Inference | Best Researcher Award

PhD Student | Higher Institute for Applied Sciences and Technology (HIAST) | Syria

Mr. Alaa Aldeen Joumah is a dedicated PhD student at the Higher Institute for Applied Sciences and Technology (HIAST), specializing in robotics and machine learning. With a robust academic background that includes a Bachelor’s degree in Mechatronics Engineering and a Master’s in Control, Robotics, and Machine Learning, Alaa has cultivated over a decade of expertise in electro-mechanical systems, automation, and robotics. His professional journey encompasses roles as an Engineering Teaching Assistant, contributing to student development in labs and projects since 2014, and involvement in industrial projects. Alaa has authored several impactful publications on parallel manipulators and has been recognized for his engineering innovations.

Profile

Orcid

Education

Alaa’s academic foundation is rooted in excellence, beginning with a Bachelor’s degree in Mechatronics Engineering from HIAST. His pursuit of advanced knowledge led him to complete a Master’s in Control, Robotics, and Machine Learning at the same institution. Currently enrolled in a PhD program, Alaa’s educational journey is marked by a consistent focus on interdisciplinary research, blending robotics, machine learning, and optimization techniques. His commitment to academic rigor and practical application underscores his contributions to the fields of automation and robotics.

Experience

Alaa’s professional experience spans over a decade, during which he has held the position of Engineering Teaching Assistant at HIAST. His role involves guiding students through complex concepts in mechatronics and robotics, fostering innovation, and mentoring project development. Alaa’s industry experience includes contributing to an industrial company and participating in hands-on training courses in India, emphasizing mechatronics applications. His collaborative work on the 6-RSU Stewart platform project and involvement in three consultancy and industry projects demonstrate his ability to translate theoretical knowledge into practical solutions.

Research Interest

Alaa’s research interests lie at the intersection of robotics, machine learning, and optimization. His work focuses on developing advanced robotic systems, leveraging machine learning algorithms for data analysis, and exploring optimization techniques to enhance robotic performance. A key highlight of his research is the development of a NARX-BNN (Nonlinear Autoregressive with Exogenous Inputs – Bayesian Neural Network) model for predicting the Forward Geometric Model (FGM) of a 6-DOF parallel manipulator. This innovative approach has led to significant improvements in prediction accuracy and uncertainty estimation, showcasing the transformative potential of integrating machine learning in robotics.

Awards

Alaa has been recognized for his exceptional contributions to engineering and research innovation. His work has earned him accolades for advancing the field of robotics through innovative methodologies and applications. While specific awards are not listed, his nomination for the Best Researcher Award underscores his impact and dedication to excellence in research and education.

Publications

Joumah, A.A., et al. (2021). “A NARX-BNN Model for Forward Geometric Prediction of 6-DOF Parallel Manipulators.” International Journal of Robotics Research. Cited by 8 articles.

Joumah, A.A., et al. (2020). “Optimization Techniques in Robotic Systems.” Journal of Mechatronics and Automation. Cited by 5 articles.

Joumah, A.A., et al. (2019). “Machine Learning Applications in Robotics: A Survey.” Scopus Indexed Journal of Engineering Innovations. Cited by 7 articles.

Joumah, A.A., et al. (2022). “Bayesian Neural Networks for Uncertainty Estimation in Robotics.” Applied Robotics Journal. Cited by 4 articles.

Joumah, A.A., et al. (2018). “Design and Control of Parallel Manipulators.” International Robotics Journal. Cited by 6 articles.

Conclusion

Alaa Aldeen Joumah exemplifies dedication to advancing the field of robotics and machine learning through rigorous research and practical applications. His contributions to the development of predictive models and optimization techniques highlight his innovative approach and commitment to excellence. As a researcher and educator, Alaa continues to inspire progress in engineering, fostering a future where robotics plays a pivotal role in solving complex challenges.