Amjad Alipanah | Mathematics | Best Researcher Award Posted on 11/06/2024 by sciencefatherLeave a Comment on Amjad Alipanah | Mathematics | Best Researcher Award Mr. Amjad Alipanah | Mathematics | Best Researcher Award PhD at University of Kurdistan, Iran. Amjad Alipanah is an esteemed Associate Professor of Applied Mathematics at the University of Kurdistan, Sanandaj, Iran. Born on September 23, 1974, he has a distinguished academic background with a BSc in Mathematics from the University of Kurdistan and both an MSc and PhD in Applied Mathematics from AmirKabir University, Tehran, Iran. His research focuses on spectral and pseudospectral methods, finite difference methods, calculus of variations, approximation theory, and numerical analysis. With a robust portfolio of journal publications and conference papers, he has significantly contributed to the field. Alipanah is also a dedicated educator, teaching a variety of undergraduate and graduate courses and supervising numerous postgraduate theses. His work has earned him top ranks as a graduate student and a prominent position in the academic community. 🌐✨ Professional Profiles: Scopus Profile ORCID Profile Education Amjad Alipanah received his Bachelor of Science (BSc) degree in Mathematics from the University of Kurdistan, Sanandaj, Iran, in 2000. He then pursued his Master of Science (MSc) in Applied Mathematics at AmirKabir University, Tehran, Iran, specializing in Partial Differential Equations with a focus on Finite Difference Methods. His master’s thesis, titled “Numerical Solution of Sine-Gordon Equation,” was supervised by Professor Mehdi Dehghan. Alipanah continued his academic journey at AmirKabir University, earning a PhD in Applied Mathematics in 2005 with a specialization in Optimal Control. His doctoral research, “Using Cardinal Functions in Spectral Methods,” was supervised by Professor Mohsen Razzaghi, with Associate Professor Mostafa Shamsi serving as his adviser. Professional Experience Amjad Alipanah currently holds the position of Associate Professor of Applied Mathematics at the University of Kurdistan in Sanandaj, Iran. His professional journey is marked by his extensive teaching and research contributions in the field of applied mathematics. Throughout his career, he has been involved in various research projects and has published numerous journal articles and conference papers on topics such as spectral and pseudospectral methods, finite difference methods, and numerical analysis. In addition to his research endeavors, Dr. Alipanah has supervised many postgraduate theses, guiding students through complex mathematical problems and innovative solutions. His commitment to education is evident through his teaching of a broad range of undergraduate and graduate courses, including Numerical Solution of Partial Differential Equations, Numerical Methods in Linear Algebra, and Advanced Numerical Analysis. 🧑🏫📊✨ Research Interest Amjad Alipanah’s research interests lie predominantly in applied mathematics, with a focus on several specialized areas. These include spectral and pseudospectral methods, which are used for solving differential equations with high accuracy; finite difference methods, which are numerical techniques for approximating solutions to differential equations; and the calculus of variations, which deals with optimizing functionals. He is also deeply engaged in approximation theory, a branch of mathematics that focuses on how functions can best be approximated with simpler functions, and numerical analysis, which involves the development and analysis of algorithms for solving mathematical problems numerically. His diverse research interests reflect his commitment to advancing mathematical methods and their applications in solving real-world problems. 📚🔢💡 Award and Honors Amjad Alipanah has received several prestigious awards and honors throughout his academic career. He graduated first in his class with a Bachelor of Science degree from the University of Kurdistan in 2000. Continuing his academic excellence, he also graduated first in his class with a Master of Science degree from AmirKabir University in Tehran, Iran, in 2002. These accolades highlight his dedication and exceptional performance in the field of mathematics. 🎓✨ Research Skills Amjad Alipanah possesses a wide range of research skills that reflect his expertise in applied mathematics. He has mastery in employing spectral and pseudospectral methods for solving differential equations and optimization problems. His proficiency in finite difference methods allows him to approximate solutions to differential equations effectively. Amjad is also skilled in the calculus of variations, which involves optimization techniques for functional analysis, crucial for understanding complex physical systems. Additionally, his expertise in approximation theory enables him to develop and analyze methods for approximating functions and solving mathematical problems. His extensive experience in numerical analysis involves the development and application of algorithms for solving mathematical problems numerically. These comprehensive skills equip him to tackle complex mathematical challenges and contribute significantly to his field. 📊🔍 Publications Numerical solution of singularly perturbed singular third-order boundary value problems with nonclassical sinc method Authors: A. Alipanah, K. Mohammadi, R.M. Haji Year: 2024 Citations: 0 On solving some stochastic delay differential equations by Daubechies wavelet Authors: N.M. Shariati, M. Yaghouti, A. Alipanah Year: 2024 Citations: 0 Numerical solution of system of second-order integro-differential equations using nonclassical sinc collocation method Authors: M. Ghasemi, K. Mohammadi, A. Alipanah Year: 2023 Citations: 3 Numerical solution of third-order singular boundary value problems with nonclassical SE-sinc-collocation and nonclassical DE-sinc-collocation Authors: A. Alipanah, K. Mohammadi, M. Shiralizadeh Year: 2023 Citations: 2 Collocation method using auto-correlation functions of compact supported wavelets for solving Volterra’s population model Authors: A. Alipanah, M. Zafari Year: 2023 Numerical solution of the system of second-order integro-differential equations using non-classical double sinc method Authors: K. Mohammadi, A. Alipanah Year: 2023 Citations: 3 Numerical solution of third-order boundary value problems using non-classical sinc-collocation method Authors: A. Alipanah, K. Mohammadi, M. Ghasemi Year: 2023 Citations: 3 Approximate solutions to the Allen–Cahn equation using rational radial basis functions method Authors: M. Shiralizadeh, A. Alipanah, M. Mohammadi Year: 2023 Citations: 1 A convergent wavelet-based method for solving linear stochastic differential equations included 1D and 2D noise Authors: N.M. Shariati, M. Yaghouti, A. Alipanah Year: 2023 Citations: 2 On the Stability of Filon–Clenshaw–Curtis Rules Authors: H. Majidian, M. Firouzi, A. Alipanah Year: 2022
Zia Bashir | Mathematics | Best Researcher Award Posted on 07/06/2024 by sciencefatherLeave a Comment on Zia Bashir | Mathematics | Best Researcher Award Assoc Prof Dr. Zia Bashir | Mathematics | Best Researcher Award Associate Professor at Quaid-i-Azam University, Pakistan. Dr. Zia Bashir is a highly accomplished mathematician with expertise in chaotic dynamical systems, game theory, and function spaces. He earned his Doctorate in Mathematics from Abdus Salam School of Mathematical Sciences, Government College University Lahore, with a commendable CGPA of 3.69 out of 4. Currently serving as an Associate Professor at Quaid-I-Azam University, Islamabad, Dr. Bashir has also held positions at the University of Central Punjab, Lahore, and the University of Sargodha, Lahore Campus. He has published extensively in prestigious international journals and actively supervises MPhil and PhD students. With proficiency in programming languages such as Python and MATLAB, along with expertise in AMS-Latex and Microsoft Office tools, Dr. Bashir excels in mathematical research and analysis. His research interests include the application of artificial intelligence tools in mathematical modeling and decision-making processes. Professional Profiles: Scopus Profile ORCID Profile Education: Dr. Zia Bashir pursued his academic journey with a strong focus on mathematics. He earned his Doctorate in Mathematics from Abdus Salam School of Mathematical Sciences, Government College University Lahore, with a commendable CGPA of 3.69 out of 4. Prior to that, he completed his Bachelor of Science in Mathematics from the Department of Mathematics, University of the Punjab, Lahore, achieving an impressive CGPA of 3.83 out of 4. His educational background equipped him with a solid foundation in mathematical theory and analytical skills, paving the way for his successful career in academia and research. Professional Experience Dr. Zia Bashir has accumulated extensive professional experience in academia, contributing significantly to the field of mathematics. Since September 2021, he has served as an Associate Professor in the Department of Mathematics at Quaid-I-Azam University, Islamabad, Pakistan. Prior to his current role, he held positions as an Assistant Professor at the same institution from September 2015 to September 2021, and as an Assistant Professor at the Faculty of IT, University of Central Punjab, Lahore, Pakistan, from September 2013 to September 2015. Additionally, he worked as a Lecturer at the University of Sargodha, Lahore Campus, Pakistan, from February 2013 to September 2013. Throughout his career, Dr. Bashir has demonstrated a commitment to academic excellence, research, and mentorship, contributing to the advancement of mathematical knowledge and education. Research Interest Dr. Zia Bashir’s research interests span a broad spectrum within mathematics, covering diverse areas such as chaotic dynamical systems with artificial intelligence tools, game theory, decision-making models, and function spaces. His work delves into understanding the dynamics of chaotic systems and their intersections with artificial intelligence techniques. Furthermore, he investigates game-theoretic frameworks and decision-making processes, aiming to analyze strategic interactions and optimize outcomes. Additionally, Dr. Bashir explores the properties and structures of various function spaces, including their embeddings, norms, and topological properties. Through his interdisciplinary approach, Dr. Bashir demonstrates a commitment to advancing mathematical knowledge and its practical applications across multiple domains. Award and Honors Dr. Zia Bashir has received several prestigious awards and honors throughout his academic career. His notable recognitions include an Honorarium of $1240 for his paper “Optimal embeddings of generalized Besov spaces” by the Eurasian Mathematical Journal. Additionally, he was awarded a commendable performance award for his outstanding performance in the 1st-year coursework at the Abdus Salam School of Mathematical Sciences. Furthermore, Dr. Bashir has been granted a Merit scholarship during his Bachelor of Science in Mathematics and received the HEC Indigenous 5000 PhD Fellowship for his MPhil leading to a Ph.D. These accolades underscore his academic excellence and dedication to advancing mathematical research. Research Skills Dr. Zia Bashir possesses a diverse range of research skills that have contributed to his success in the field of mathematics. He is proficient in conducting advanced mathematical analyses and has a deep understanding of various mathematical concepts and theories. His expertise extends to areas such as chaotic dynamical systems, game theory, function spaces, and decision-making models. Dr. Bashir is skilled in utilizing artificial intelligence tools to study complex systems and has a strong background in computational mathematics. He is adept at designing and implementing mathematical models to address real-world problems and has demonstrated proficiency in programming languages such as Python and MATLAB. Additionally, Dr. Bashir is experienced in using AMS-Latex for writing mathematical documents and Microsoft Office tools for data analysis and presentation. His comprehensive research skills enable him to make significant contributions to the field of mathematics and address complex scientific challenges effectively. Publications Chaos analysis of nonlinear variable order fractional hyperchaotic Chen system utilizing radial basis function neural network Authors: S. Hussain, Z. Bashir, M.G.A. Malik Journal: Cognitive Neurodynamics, 2024 Citations: 0 Exploring the stochastic patterns of hyperchaotic Lorenz systems with variable fractional order and radial basis function networks Authors: M. Awais, M.A. Khan, Z. Bashir Journal: Cluster Computing, 2024 Citations: 0 Image pixels swapping encryption based on the TetraVex game and a publicly hash-sharing algorithm Authors: M. Hussain, N. Iqbal, Z. Bashir Journal: Cluster Computing, 2024 Citations: 1 A cubic q-rung orthopair fuzzy TODIM method based on Minkowski-type distance measures and entropy weight Authors: J. Ali, Z. Bashir, T. Rashid Journal: Soft Computing, 2023, 27(20), pp. 15199–15223 Citations: 5 A q-rung orthopair hesitant fuzzy stochastic method based on regret theory with unknown weight information Authors: J. Ali, Z. Bashir, T. Rashid, W.K. Mashwani Journal: Journal of Ambient Intelligence and Humanized Computing, 2023, 14(9), pp. 11935–11952 Citations: 13 A study on the normality of Wijsman topology of a fuzzy metric space Authors: Z. Bashir, A. Ullah Journal: Soft Computing, 2023, 27(1), pp. 17–23 Citations: 1 A chaotic image encryption scheme based on multi-directional confusion and diffusion operations Authors: M. Hussain, N. Iqbal, Z. Bashir Journal: Journal of Information Security and Applications, 2022, 70, 103347 Citations: 10 A multi-criteria group decision-making approach based on revised distance measures under dual hesitant fuzzy setting with unknown weight information Authors: J. Ali, Z. Bashir, T. Rashid Journal: Soft Computing, 2022, 26(17), pp. 8387–8401 Citations: 8 Asymptotic Analysis of Low Energy Extremals with Γ-Convergence in Variable Exponent Lebesgue Spaces Authors: A. Siddique, A. Shekhovtsov, Z. Bashir, W. Sałabun Journal: Fractal and Fractional, 2022, 6(3), 128 Citations: 0 On distance measure and TOPSIS model for probabilistic interval-valued hesitant fuzzy sets: application to healthcare facilities in public hospitals Authors: J. Ali, Z. Bashir, T. Rashid Journal: Grey Systems, 2022, 12(1), pp. 197–229 Citations: 17
Ayyub Sheikhi | Mathematics | Best Researcher Award Posted on 01/06/202403/06/2024 by sciencefatherLeave a Comment on Ayyub Sheikhi | Mathematics | Best Researcher Award Assoc Prof Dr. Ayyub Sheikhi | Mathematics | Best Researcher Award Department of Statistics at Shahid Bahonar University of Kerman, Iran. Ayyub Sheikhi possesses a robust set of research skills honed through years of academic and professional experience. Proficient in both theoretical and applied aspects of statistics and data science, he excels in experimental design, statistical analysis, and modeling techniques. Ayyub demonstrates proficiency in various statistical software packages, including R, and is adept at implementing advanced methodologies such as machine learning algorithms and Bayesian inference. His research skills also extend to data visualization and interpretation, allowing him to effectively communicate complex statistical findings to diverse audiences. Ayyub’s expertise in statistical research methodologies is further augmented by his ability to collaborate across interdisciplinary teams and lead projects from conception to completion. With a keen attention to detail and a commitment to methodological rigor, Ayyub Sheikhi continues to make significant contributions to the advancement of statistical science. Professional Profiles: Scopus Profile Google Scholar Education Ayyub Sheikhi pursued his academic journey in statistics and applied mathematics, earning his Ph.D. in Applied Mathematics from Shahid Bahonar University of Kerman, Iran, in 2012. Prior to that, he completed his Master of Science in Statistics at AmirKabir University of Technology, Tehran, Iran, and his Bachelor of Science in Statistics at Shahid Bahonar University of Kerman. His educational background equipped him with a strong foundation in mathematical and statistical principles, which he has since applied in both academic and professional settings, contributing significantly to the field of statistics and data science. Professional Experience Ayyub Sheikhi has garnered extensive professional experience in academia, research, and leadership roles. From 2018 to 2020, he served as the Head of the Department of Statistics at Shahid Bahonar University of Kerman, Iran, where he demonstrated his leadership skills in managing departmental affairs and fostering academic excellence. Concurrently, since 2015, he has held the position of Assistant Professor in the Department of Statistics at the same university, contributing to both teaching and research activities. In 2020, he was promoted to the position of Associate Professor, recognizing his scholarly achievements and expertise in the field. Additionally, since 2021, Ayyub has taken on the role of Head of the “Data Mining and Machine Learning” group at the Mahani Mathematical Research Institute, Shahid Bahonar University of Kerman, further showcasing his commitment to advancing statistical research and methodologies. Moreover, he has enriched his professional experience through a research fellowship at the University of Plymouth, UK, during the academic year 2023-2024, broadening his perspective and collaborating with international scholars in the field of statistics and data science. Research Interest Ayyub Sheikhi’s research interests encompass a diverse array of topics within the field of statistics and data science. He is particularly interested in Bayesian methods, change-point detection, and dynamic time series analysis, exploring innovative approaches to model complex data structures and uncover temporal patterns. Additionally, he focuses on copula-related techniques for analyzing dependence structures in multivariate data, aiming to develop robust methodologies for financial modeling and risk management. Ayyub also investigates machine learning methods, such as clustering algorithms and support vector machines, with a specific focus on their applications in outlier detection, classification, and regression tasks. Furthermore, he is keen on exploring the intersection of statistics with other disciplines, including economics, medicine, and engineering, to address real-world challenges and advance interdisciplinary research initiatives. Overall, Ayyub’s research interests reflect his dedication to advancing statistical theory and methodology while addressing practical problems across various domains. Award and Honors Ayyub Sheikhi, a prominent figure in the field of statistics and data science, has accumulated a wealth of experience and expertise over the years. He has held various academic and research positions, including serving as the Head of the Department of Statistics at Shahid Bahonar University of Kerman, Iran, from 2018 to 2020, and as an Assistant Professor and later an Associate Professor in the same department. Ayyub’s academic journey began with a Ph.D. in Applied Mathematics from Shahid Bahonar University of Kerman, Iran, in 2012, complemented by an M.Sc. in Statistics from AmirKabir University of Technology, Tehran, and a B.Sc. in Statistics from Shahid Bahonar University of Kerman. His scholarly contributions extend beyond academia, as evidenced by his involvement in various visiting appointments, publication of books, development of statistical packages, and leadership in research projects. Ayyub’s commitment to excellence and innovation in statistics continues to drive advancements in the field, positioning him as a respected authority and mentor within the academic community. Research Skills Dr. Sheikhi Ayyub possesses a breadth of research skills spanning statistical and mathematical domains, underpinned by a dedication to practical problem-solving. His expertise encompasses statistical inference, where he adeptly employs hypothesis testing, estimation, and model fitting to derive meaningful insights from data. Proficient in data analysis techniques, Dr. Ayyub excels in uncovering patterns and trends within complex datasets, thereby facilitating informed decision-making processes. Moreover, he demonstrates a keen understanding of machine learning algorithms, employing them for tasks ranging from classification and regression to clustering and anomaly detection, thereby enhancing predictive modeling capabilities. Additionally, Dr. Ayyub showcases proficiency in time series analysis, employing various techniques to analyze temporal data, identify patterns, and forecast future values effectively. Furthermore, his expertise extends to Bayesian statistics, copula models, and robust statistical methods, further enriching his analytical toolkit. Proficient in utilizing statistical software packages like R, Python, and MATLAB, Dr. Ayyub applies these skills across interdisciplinary research endeavors, contributing to advancements in fields ranging from healthcare and economics to engineering and finance. Publications A two-stage Bridge estimator for regression models with endogeneity based on control function method Authors: Bahador, F., Sheikhi, A., Arabpour, A. Year: 2024 Journal: Computational Statistics Volume: 39 Issue: 3 Pages: 1351–1370 Citations: 0 Convex weak concordance measures and their constructions Authors: Mesiar, R., Kolesárová, A., Sheikhi, A., Shvydka, S. Year: 2024 Journal: Fuzzy Sets and Systems Volume: 478 Pages: 108841 Citations: 1 Multivariate Asymmetric Distributions of Copula Related Random Variables Authors: Sheikhi, A., Arad, F., Mesiar, R. Year: 2023 Journal: Austrian Journal of Statistics Volume: 52 Issue: 4 Pages: 1–14 Citations: 0 A dimension reduction in neural network using copula matrix Authors: Sheikhi, A., Mesiar, R., Holeňa, M. Year: 2023 Journal: International Journal of General Systems Volume: 52 Issue: 2 Pages: 131–146 Citations: 3 Convex concordance measures Authors: Mesiar, R., Kolesárová, A., Sheikhi, A. Year: 2022 Journal: Fuzzy Sets and Systems Volume: 441 Pages: 366–377 Citations: 2 Copula-based Berkson measurement error models Authors: Ziaei, A.R., Zare, K., Sheikhi, A. Year: 2022 Journal: Iranian Journal of Fuzzy Systems Volume: 19 Issue: 4 Pages: 165–175 Citations: 0 A heteroscedasticity diagnostic of a regression analysis with copula dependent random variables Authors: Sheikhi, A., Arad, F., Mesiar, R. Year: 2022 Journal: Brazilian Journal of Probability and Statistics Volume: 36 Issue: 2 Pages: 408–419 Citations: 0 ON ASYMMETRIC DISTRIBUTIONS OF COPULA RELATED RANDOM VARIABLES WHICH INCLUDES THE SKEW-NORMAL ONES Authors: Sheikhi, A., Arad, F., Mesiar, R. Year: 2022 Journal: Kybernetika Volume: 58 Issue: 6 Pages: 984–995 Citations: 1 Asymmetric distributions based on the t-copula Authors: Arad, F., Sheikhi, A. Year: 2022 Conference: 9th Iranian Joint Congress on Fuzzy and Intelligent Systems, CFIS 2022 Citations: 0 On a generalization of the test of endogeneity in a two stage least squares estimation Authors: Sheikhi, A., Bahador, F., Arashi, M. Year: 2022 Journal: Journal of Applied Statistics Volume: 49 Issue: 3 Pages: 709–721 Citations: 11