Muhammad Tahir | Mathematics | Young Scientist Award

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Dr. Muhammad Tahir | Mathematics | Young Scientist Award

Gomal University | Pakistan

Dr. Muhammad Tahir is an emerging researcher and academic in the field of applied mathematics, with expertise spanning numerical analysis, fuzzy logic, artificial intelligence, and decision-making systems. He has served as a Lecturer in Mathematics at Beacon Light College, Pakistan, and as a Teaching Assistant at the Islamia University of Bahawalpur, where he contributed to curriculum development and quality enhancement initiatives. Dr. Tahir holds a Master of Science in Mathematics from the Islamia University of Bahawalpur, where his thesis focused on the “Numerical Study of Deformation of Bubbles Using Phase-Field Models with Decoupling Technique.” His research portfolio includes several high-impact publications in reputed journals such as Applied Soft Computing, European Journal of Pure and Applied Mathematics, and Engineering Applications of Artificial Intelligence. His studies cover topics like fuzzy set theory, cryptographic security, cyber risk mitigation, environmental sustainability, and multi-criteria decision-making. Dr. Tahir’s recent works emphasize hybrid intelligence frameworks, machine learning-integrated decision systems, and quantum-resistant cryptography. He has presented his research at international conferences in Turkey, demonstrating his commitment to interdisciplinary collaboration and computational innovation. His scholarly contributions continue to advance soft computing, mathematical modeling, and intelligent decision-making for industrial and environmental applications.

Profiles : Scopus | Orcid

Featured Publications

Kamran, M., Zhang, Q., Pamucar, D., Tahir, M., & Simic, V. (2025). Enhancing confidence level in decision-making frameworks using Fermatean fuzzy rough sets: Application in Industry 4.0. Applied Soft Computing.

Tahir, M., Kfueit, K., Rasheed, M., Hanan, A., & Shahid, M. I. (2025, October 4). Pythagorean soft sets and hypersoft sets: A comprehensive framework for advanced uncertainty modeling in decision making. Spectrum of Decision Making and Applications.

Gwo Dong Lin | Mathematics | Excellence in Research Award

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Prof. Gwo Dong Lin | Mathematics | Excellence in Research Award

Academia Sinica, Institute of Statistical Science | Taiwan

Prof. Gwo Dong Lin is a distinguished statistician and mathematician whose extensive contributions have profoundly influenced the fields of probability theory, moment problems, and life distribution analysis. With an h-index of 18, 71 published documents, and 933 citations from 783 sources, his scholarly output demonstrates both depth and enduring impact. He earned his Ph.D. in Management Science from Tamkang University, following earlier degrees in mathematics from National Taiwan Normal University. Over his career, Prof. Lin served at Academia Sinica’s Institute of Statistical Science, including roles as Deputy Director and Acting Director, and later as Adjunct Research Fellow. He has also directed the Social and Data Science Research Center under the Hwa-Kang Xing-Ye Foundation. His editorial work spans several international journals, and he has been an invited speaker at global conferences organized by the International Statistical Institute and other leading organizations. Recognized as an ISI Elected Member since 1991 and recipient of Taiwan’s Outstanding Research Award (1994–1995), Prof. Lin’s pioneering studies on characterizations of distributions, inequalities for transforms, and moment determinacy continue to shape modern statistical theory and inspire future explorations in applied probability and statistical modeling.

Profile : Scopus

Featured Publications 

Lin, G. D., & Stoyanov, J. (2025). New sufficient conditions for moment-determinacy via probability density tails. Mathematics, 13, 2671.

Dou, X., Kuriki, S., Lin, G. D., & Richards, D. (2025). EM estimation of the B-spline copula with penalized pseudo-likelihood functions. Statistical Papers, 66, 30.

Lin, G. D., & Stoyanov, J. (2024). New characterizations of the Gamma distribution via independence of two statistics by using Anosov’s theorem. Theory of Probability and Its Applications, 69, 745–759 (Russian edition); SIAM version, 69, 592–604.

Hu, C.-Y., & Lin, G. D. (2022). Characterizations of the normal distribution via the independence of the sample mean and the feasible definite statistics with ordered arguments. Annals of the Institute of Statistical Mathematics, 74, 473–488.

Lin, G. D., & Hu, C.-Y. (2022). On the semi-Mittag-Leffler distributions. Probability and Mathematical Statistics, 42, 81–96.

Hu, C.-Y., Lin, G. D., & Stoyanov, J. (2021). Characterization of probability distributions via functional equations of power-mixture type. Mathematics, 9, 271. Also in: L. Shaikhet (Ed.), Prime Archives in Applied Mathematics (2nd ed.). Hyderabad, India: Vide Leaf.

Lin, G. D., & Dou, X. (2021). An identity for two integral transforms applied to the uniqueness of a distribution via its Laplace–Stieltjes transform. Statistics, 55, 365–385.

Dou, X., Kuriki, S., Lin, G. D., & Richards, D. (2021). Dependence structures of B-spline copulas. Sankhyā: The Indian Journal of Statistics, Series A, 83, 238–311.

Lin, G. D., & Hu, C.-Y. (2021). Formulas of absolute moments. Sankhyā: The Indian Journal of Statistics, Series A, 83, 476–495.

Hu, C.-Y., & Lin, G. D. (2020). Necessary and sufficient conditions for unique solution to functional equations of Poincaré type. Journal of Mathematical Analysis and Applications, 491, 124399.

Stoyanov, J. M., Lin, G. D., & Kopanov, P. (2020). New checkable conditions for moment determinacy of probability distributions. Theory of Probability and Its Applications, 65, 634–648 (Russian edition); SIAM version, 65, 497–509.

Lin, G. D., Dou, X., & Kuriki, S. (2019). The bivariate lack-of-memory distributions. Sankhyā: The Indian Journal of Statistics, Series A, 81, 273–297.

Lin, G. D. (2019). On powers of the Catalan number sequence. Discrete Mathematics, 342, 2139–2147.

Hu, C.-Y., & Lin, G. D. (2018). Characterizations of the logistic and related distributions. Journal of Mathematical Analysis and Applications, 463, 79–92.

Lin, G. D. (2017). Recent developments on the moment problem. Journal of Statistical Distributions and Applications, 4, 5.

Lai, C.-D., Lin, G. D., Govindaraju, K., & Pirikahu, S. (2017). A simulation study on the correlation structure of Marshall–Olkin bivariate Weibull distribution. Journal of Statistical Computation and Simulation, 87, 156–170.

Hassan Ramchoun | Mathematics | Best Researcher Award

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Dr. Hassan Ramchoun | Mathematics | Best Researcher Award

Moulay Ismail University | Morocco

Author Profile

Scopus

Early Academic Pursuits

Dr. Hassan Ramchoun’s academic journey reflects a strong foundation in mathematics and computer science. Beginning with his bachelor’s studies in applied mathematics, he progressively advanced through a master’s degree in operations research and statistics, where he explored Bayesian approaches in artificial neural networks for medical imaging. His doctoral research in applied mathematics and computer science further solidified his expertise, focusing on parameter and hyper-parameter estimation in Bayesian neural networks with applications in classification and regression. These early experiences shaped his specialization in applied mathematics, artificial intelligence, and machine learning.

Professional Endeavors

Dr. Ramchoun has built a diverse academic career with teaching, research, and leadership responsibilities. Since joining ENCG Meknès, Moulay Ismail University, as a lecturer, he has also taught at multiple institutions including ENSAM Meknès and the Euro-Mediterranean University of Fès. His teaching portfolio covers a wide spectrum, from probability and statistics to optimization, data analysis, and artificial intelligence. His active engagement in curriculum design, supervision of students, and participation in doctoral juries reflects his deep commitment to higher education and student mentorship.

Contributions and Research Focus

Dr. Ramchoun’s research focuses on applied mathematics, artificial intelligence, and data science, with particular emphasis on Bayesian neural networks, deep learning, optimization, and statistical learning methods. He has contributed to developing new methods for training and optimizing neural networks, incorporating regularization and Bayesian inference. His work extends to multi-objective optimization for neural architectures, convolutional neural networks, and applications in big data analytics. His scholarly contributions are reflected in numerous publications in international journals and conferences, alongside editorial contributions to Springer volumes on artificial intelligence and industrial applications.

Accolades and Recognition

Dr. Ramchoun’s academic excellence has been acknowledged through distinctions such as the CNRST excellence research scholarship and his recognition for doctoral work with high honors. His research output is regularly published in reputed international journals including Neurocomputing, Knowledge-Based Systems, Soft Computing, and Evolving Systems. His active involvement as a reviewer for leading journals and as a member of scientific committees of conferences demonstrates recognition of his expertise by the global scientific community.

Impact and Influence

Through his work, Dr. Ramchoun has significantly influenced both the academic and applied dimensions of artificial intelligence. His innovations in neural network optimization and Bayesian learning methods have advanced understanding in machine learning research, while his teaching and supervision of master’s and doctoral students have contributed to developing future generations of researchers. By bridging theoretical modeling with practical applications, his contributions have relevance not only in academia but also in applied domains such as data science, robotics, and image processing.

Legacy and Future Contributions

The legacy of Dr. Ramchoun lies in his efforts to advance the integration of applied mathematics with artificial intelligence, particularly in deep learning and Bayesian modeling. His involvement in research projects, scientific committees, and international conferences ensures that his contributions extend beyond publications to shaping the field itself. Looking forward, his continued work in optimization techniques, advanced statistical learning, and interdisciplinary applications promises to strengthen the role of artificial intelligence in addressing scientific and industrial challenges.

Publications

  • Article: Convergence of batch gradient descent with learnable smooth masks for pruning feedforward neural networks
    Authors: Quasdane, M., Ramchoun, H., Masrour, T.
    Journal: Neurocomputing
    Year: 2025

  • Article: Enhancing CNN structure and learning through NSGA-II-based multi-objective optimization
    Authors: Elghazi, Khalid, Ramchoun, Hassan, Masrour, Tawfik
    Journal: Evolving Systems
    Year: 2024

  • Article: Implicitly adaptive optimal proposal in variational inference for Bayesian learning
    Authors: Bakhouya, Mostafa, Ramchoun, Hassan, Hadda, Mohammed, et al.
    Journal: International Journal of Data Science and Analytics
    Year: 2024

  • Article: Gaussian Mixture Models for Training Bayesian Convolutional Neural Networks
    Authors: Bakhouya, M., Ramchoun, H., Hadda, M., Masrour, T.
    Journal: Evolutionary Intelligence (Springer)
    Year: 2024

  • Article: Sparse smooth group L0L1/2 regularization method for convolutional neural networks
    Authors: Quasdane, M., Ramchoun, H., Masrour, T.
    Journal: Knowledge-Based Systems
    Year: 2023

Conclusion

Dr. Hassan Ramchoun exemplifies the qualities of a dedicated academic, innovative researcher, and committed educator. His career reflects a balance of teaching excellence, impactful research, and institutional service. With strong foundations in mathematics and expertise in artificial intelligence, his contributions are shaping the evolving landscape of machine learning and data science. His recognition, publications, and leadership in academic communities confirm his standing as an influential figure whose work will continue to resonate in both research and applied domains.

Okechukwu Obulezi | Mathematics | Editorial Board Member

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Dr. Okechukwu Obulezi | Mathematics | Editorial Board Member

Nnamdi Azikiwe University | Nigeria

Author Profile

Scopus

Orcid

🎓 Early Academic Pursuits

Dr. Okechukwu Obulezi began his academic journey with a focus on statistical sciences, obtaining an ND in Statistics from Abia State Polytechnic in 2006. Driven by his passion, he continued with an HND in Statistics from the same institution, culminating in a strong foundation in quantitative analysis and data interpretation. Pursuing higher learning, he completed a PGD in Statistics at Nnamdi Azikiwe University in 2012, with a thesis on the "Discriminant Analysis of the Nigerian Fixed Assets." His master's thesis focused on "BIC-Based Relative Influence Measure for Outlier Detection and Variable Selection in Regression Analysis," setting the stage for his current Ph.D. in Statistics, where he explores complex statistical methods for predictive and analytical modeling.

💼 Professional Endeavors

Dr. Obulezi’s professional career spans several academic roles, starting as an Instructor at Abia State Polytechnic in 2011, where he advanced to Senior Instructor by 2015. In 2019, he joined Nnamdi Azikiwe University as an Assistant Lecturer in the Statistics Department, quickly progressing to Lecturer II and then Lecturer I by 2023. His responsibilities include teaching specialized courses such as Biostatistics, Statistical Methods, Probability Theory, and Matrix Algebra, where he imparts knowledge to the next generation of statisticians. Beyond teaching, he plays critical roles in advising undergraduates, coordinating seminars and projects, and contributing to departmental committees, such as the Faculty ICT Committee and Faculty Repair and Maintenance Committee.

🔬 Contributions and Research Focus

Dr. Obulezi’s research interests lie at the intersection of probability distributions, machine learning, and statistical modeling, with applications in survival analysis, acceptance sampling, and censored data analysis. His contributions to these fields include publications in high-impact journals, focusing on new statistical models for various real-world applications. Some of his significant research includes new distribution models for engineering, biomedical, and environmental data, optimization of GARCH models for financial volatility, and innovative sampling plans for reliability testing. His publications reflect his commitment to advancing the fields of statistics and machine learning by creating robust, practical solutions for complex data challenges.

🏆 Accolades and Recognition

Dr. Obulezi has earned recognition for his academic and research excellence, serving as a reviewer for several prestigious journals, such as Cogent Engineering, Scientific African, and Alexandria Engineering Journal. His expertise has also led him to contribute as a reviewer for academic book chapters, particularly in mathematical and computer science research. This engagement underscores his prominence as a thought leader in the statistical community and highlights the respect he commands among peers for his critical insights and expertise.

🌍 Impact and Influence

Dr. Obulezi's work in developing statistical models and distributions has had a significant impact, particularly in the areas of biomedicine, engineering, and environmental science. His innovative methodologies have helped refine statistical tools for better data analysis, contributing to improved outcomes in public health research, environmental risk assessment, and financial risk management. His influence also extends to mentoring students and collaborating with other academics, which enriches the statistical field and inspires the next generation of statisticians.

🔮 Legacy and Future Contributions

Looking forward, Dr. Obulezi aims to further his research in advanced statistical modeling, focusing on machine learning applications and data-driven decision-making in complex fields. His commitment to exploring new statistical approaches for big data and predictive analysis places him at the forefront of his field, positioning him to make enduring contributions that will drive innovation in statistical methodologies and applications for years to come.

 

Publications

  • 📄 Parameter estimation for reduced Type-I Heavy-Tailed Weibull distribution under progressive Type-II censoring scheme
  • Authors: Prakash, A., Maurya, R.K., Alsadat, N., Obulezi, O.J.
  • Journal: Alexandria Engineering Journal
  • Year: 2024
  • 📄 Sine generalized family of distributions: Properties, estimation, simulations and applications
  • Authors: Oramulu, D.O., Alsadat, N., Kumar, A., Bahloul, M.M., Obulezi, O.J.
  • Journal: Alexandria Engineering Journal
  • Year: 2024
  • 📄 A more flexible Lomax distribution: Characterization, estimation, group acceptance sampling plan and applications
  • Authors: Ekemezie, D.-F.N., Alghamdi, F.M., Aljohani, H.M., El-Raouf, M.M.A., Obulezi, O.J.
  • Journal: Alexandria Engineering Journal
  • Year: 2024
  • 📄 A new extension of Burr-Hatke exponential distribution with engineering and biomedical applications
  • Authors: Anyiam, K.E., Alghamdi, F.M., Nwaigwe, C.C., Aljohani, H.M., Obulezi, O.J.
  • Journal: Heliyon
  • Year: 2024
  • 📄 Group acceptance sampling plan based on truncated life tests for Type-I heavy-tailed Rayleigh distribution
  • Authors: Nwankwo, M.P., Alsadat, N., Kumar, A., Bahloul, M.M., Obulezi, O.J.
  • Journal: Heliyon
  • Year: 2024

 

Abayneh Fantaye | Mathematics | Editorial Board Member

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Mr. Abayneh Fantaye | Mathematics | Editorial Board Member

Debre Tabor University | Ethiopia

Author Profile

Google Scholar

Early Academic Pursuits

Abayneh Kebede Fantaye embarked on his academic journey at Anole Elementary School, where he excelled in Mathematics, Ethical Education, Physics, Biology, Chemistry, History, and Geography. His passion for learning led him to Gado Guna Secondary School, earning the Ethiopian General Secondary Education Certificate. Furthering his academic prowess, he completed the Ethiopian Higher Education Entrance Qualification Certificate at Asella Preparatory School.

Professional Endeavors

Abayneh's pursuit of knowledge continued at Debre Tabor University, where he earned a Bachelor's degree in Mathematics. His comprehensive coursework included areas such as Algebra, Calculus, Statistics, Linear Optimization, Differential Equations, and more. Undeterred by challenges, he pursued a Master's degree at Hawassa University in Mathematical and Statistical Modeling, delving into advanced topics like Numerical Mathematics, Differential Equations, Bayesian Data Inference, and Statistical Methods.

Contributions and Research Focus

As a dedicated lecturer at Debre Tabor University, Abayneh contributes significantly to the academic landscape. His research focus spans Numerical Optimization, Differential Equations, Dynamical Systems, and Mathematical Modeling. He brings a wealth of knowledge to his students, fostering a deep understanding of mathematical concepts and their real-world applications.

Accolades and Recognition

Abayneh's commitment to academic excellence has earned him accolades, including the Primary School Leaving Certificate and the Ethiopian General Secondary Education Certificate. His pursuit of a Master's degree further underscores his dedication to advancing his expertise in Mathematics and Statistical Modeling.

Impact and Influence

Through his role as a lecturer, Abayneh influences the next generation of mathematicians. His commitment to providing a holistic education that combines theoretical knowledge with practical applications leaves a lasting impact on his students.

Legacy and Future Contributions

Abayneh Kebede Fantaye's legacy is one of academic rigor, continuous learning, and a passion for mathematics. His future contributions are poised to extend beyond the classroom, enriching mathematical research and fostering an environment where students thrive in the world of numbers.

Notable Publications

Mathematical Model and Analysis of Corruption Dynamics with Optimal Control 2022 (13)

ECO-EPIDEMIOLOGICAL MODEL AND STABILITY ANALYSIS OF COTTON LEAF CURL VIRUS (CLCUV) TRANSMISSION DYNAMICS 2022 (2)

Mathematical Model and Stability Analysis on the Transmission Dynamics of Skin Sores 2022 (1)