Zia Bashir | Mathematics | Best Researcher Award

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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:

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

  1. 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
  2. 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
  3. 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
  4. 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. 15199ā€“15223
    • Citations: 5
  5. A q-rung orthopair hesitant fuzzy stochastic method based on regret theory with unknown weight information
    1. Authors: J. Ali, Z. Bashir, T. Rashid, W.K. Mashwani
    2. Journal: Journal of Ambient Intelligence and Humanized Computing, 2023, 14(9), pp. 11935ā€“11952
    3. Citations: 13
  6. 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. 17ā€“23
    • Citations: 1
  7. 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
  8. 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. 8387ā€“8401
    • Citations: 8
  9. Asymptotic Analysis of Low Energy Extremals with Ī“-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
  10. On distance measure and TOPSIS model for probabilistic interval-valued hesitant fuzzy sets: application to healthcare facilities in public hospitals
    1. Authors: J. Ali, Z. Bashir, T. Rashid
    2. Journal: Grey Systems, 2022, 12(1), pp. 197ā€“229
    3. Citations: 17

 

Ayyub Sheikhi | Mathematics | Best Researcher Award

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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:

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

  1. 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: 1351ā€“1370
    • Citations: 0
  2. Convex weak concordance measures and their constructions
    • Authors: Mesiar, R., KolesĆ”rovĆ”, A., Sheikhi, A., Shvydka, S.
    • Year: 2024
    • Journal: Fuzzy Sets and Systems
    • Volume: 478
    • Pages: 108841
    • Citations: 1
  3. 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: 1ā€“14
    • Citations: 0
  4. 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: 131ā€“146
    • Citations: 3
  5. Convex concordance measures
    • Authors: Mesiar, R., KolesĆ”rovĆ”, A., Sheikhi, A.
    • Year: 2022
    • Journal: Fuzzy Sets and Systems
    • Volume: 441
    • Pages: 366ā€“377
    • Citations: 2
  6. 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: 165ā€“175
    • Citations: 0
  7. 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: 408ā€“419
    • Citations: 0
  8. 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: 984ā€“995
    • Citations: 1
  9. 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
  10. 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: 709ā€“721
    • Citations: 11