Burak Karabey | Mathematics Education | Best Researcher Award

Published on by Top Teachers

Best Researcher Award

Burak Karabey
Dokuz Eylul University, Turkey
Burak Karabey
Affiliation Dokuz Eylul University
Country Turkey
Scopus ID 15061474600
Documents 6
Citations 19
h-index 3
Subject Area Mathematics Education
Event Top Teachers Awards
ORCID 0000-0001-8614-8628
Google Scholar ZRFPgggAAAAJ

Burak Karabey is a Turkish scholar in mathematics education, gifted education, STEAM learning, curriculum development, and teacher training. His academic career at Dokuz Eylul University spans teaching, research, project leadership, curriculum innovation, and public engagement. Through national and international initiatives supported by governmental agencies, European Union programs, and educational organizations, he has contributed to the advancement of mathematics education and gifted student development in Türkiye.[1]

Abstract

This article summarizes the academic achievements, research activities, publications, leadership roles, and educational contributions of Burak Karabey. His work focuses on mathematics education, gifted education, STEAM learning, curriculum design, and teacher professional development. Through scholarly publications, funded projects, curriculum initiatives, and public outreach, he has contributed to educational innovation and the development of learning frameworks in Türkiye.[1]

Keywords

Mathematics Education, Giftedness, STEM Education, STEAM Education, Instructional Design, Curriculum Development, Teacher Training, Educational Innovation.

Introduction

After graduating from the Department of Mathematics Education in 2001, Karabey completed graduate and doctoral studies at Dokuz Eylul University, focusing on geometry, mathematical creativity, gifted education, and critical thinking. His academic development led to long-term involvement in curriculum reform, teacher education, and research concerning gifted learners and mathematics instruction.[1]

Research Profile

Burak Karabey serves as Associate Professor at Dokuz Eylul University and has held multiple academic leadership positions. His research areas include social sciences and humanities, elementary education, special education, mathematics education, gifted education, teacher training, curriculum development, scientific thinking, and STEAM-based instructional approaches. He has also contributed extensively to public science communication through articles, conferences, and media appearances.[1]

Research Contributions

His contributions include curriculum development for gifted students, mathematics framework design, STEAM competency development, inquiry-based mathematics teaching, and educational policy initiatives. He has participated as coordinator, executive, expert, trainer, and researcher in projects supported by TÜBİTAK, UNICEF, Erasmus+, the Ministry of National Education, and other organizations. These projects contributed to nationwide curriculum implementation, teacher capacity building, and educational innovation across Türkiye.

  • Development of gifted education curricula for K–12 education.
  • Mathematics curriculum coordination within the Türkiye Holistic Model Skills Framework.
  • Leadership in summer and winter school mathematics curriculum initiatives.
  • European Union projects on STEAM competencies and intercultural education.
  • Professional development programs for teachers of gifted students.

Publications

Burak Karabey’s publications examine giftedness, mathematical creativity, critical thinking, STEAM education, curriculum development, and teacher preparation, contributing evidence-based perspectives that support innovation in mathematics education and educational practice.[2][3][4][5][6]

  1. Creativity and Giftedness Evaluated from the Perspective of Some Theories of Intelligence.[2]
  2. Determining the Achievement Levels of Gifted Primary School Students in Creative Problem Solving and Critical Thinking Skills.[3]
  3. Discovering Complementary Colors from the Perspective of STEAM Education.[4]
  4. The Effect of Problem-Based Learning on Pre-Service Mathematics Teachers’ Success in Measurement and Vectors Topics.[5]
  5. K12 Skills Framework Türkiye Holistic Model Mathematics Field Skills.[6]

Research Impact

The impact of Burak Karabey’s work extends beyond scholarly publication into curriculum implementation, teacher education, gifted student support, and educational policy. His participation in national curriculum initiatives and international collaborations demonstrates sustained influence on educational practice and innovation. His research has also supported evidence-based approaches to creativity, critical thinking, and mathematics learning among gifted students.[2][3]

Award Suitability

Burak Karabey demonstrates characteristics associated with academic recognition through sustained scholarly productivity, curriculum leadership, interdisciplinary collaboration, project management, teacher education, and public engagement. His contributions to gifted education, mathematics education, STEAM initiatives, and national curriculum development provide a substantial record of service and impact that aligns with the objectives of the Top Teachers Awards program.

Conclusion

Burak Karabey has established a professional profile combining research, educational leadership, curriculum development, and public scholarship. His work reflects a sustained commitment to mathematics education, gifted student development, teacher training, and educational innovation. Through academic publications and major educational projects, he continues to contribute to the advancement of learning and teaching practices in Türkiye and beyond.

References

  1. Elsevier. (n.d.). Scopus author details: Burak Karabey, Author ID 15061474600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=15061474600
  2. Karabey, B., & Yürümezoğlu, K. Creativity and Giftedness Evaluated from the Perspective of Some Theories of Intelligence. https://dergipark.org.tr/en/pub/deubefd/article/265089
  3. Karabey, B. Determining the Achievement Levels of Gifted Primary School Students in Creative Problem Solving and Critical Thinking Skills. https://www.proquest.com/openview/bab8707abdd3e4127d146ec0ec7f9584/1
  4. Karabey, B., et al. Discovering Complementary Colors from the Perspective of STEAM Education. Physics Education. DOI: https://doi.org/10.1088/1361-6552/aa97bf
  5. Selçuk, G., Karabey, B., & Çalışkan, S. The Effect of Problem-Based Learning on Pre-Service Mathematics Teachers’ Success in Measurement and Vectors Topics. https://dergipark.org.tr/tr/pub/mkusbed/article/208674
  6. Karabey, B., & Erdoğan, A. K12 Skills Framework Türkiye Holistic Model Mathematics Field Skills. https://dergipark.org.tr/en/pub/milliegitim/article/1309180

Muhammad Farhan | Mathematics | Best Researcher Award

Published on by Top Teachers

Best Researcher Award

Muhammad Farhan — Yangzhou University

Muhammad Farhan
Affiliation Yangzhou University
Country Pakistan
Scopus ID 59432913900
Documents 41
Citations 477
h-index 11
Subject Area Mathematics
Event Top Teachers Awards
ORCID 0000-0002-2235-0015
Google Scholar IBTzbUAAAAJ

Muhammad Farhan is a mathematician and researcher affiliated with Yangzhou University whose work focuses on infectious disease dynamics, nonlinear mathematical systems, artificial intelligence integration, and computational epidemiology. His academic profile includes research contributions involving fractional-order differential equations, neural network frameworks, and data-driven disease modeling methodologies within applied mathematics and computational science.[1]

Abstract

This article summarizes the academic profile, scientific contributions, and research activities of Muhammad Farhan in the field of mathematics and computational disease modeling. His work combines nonlinear differential equations, stochastic artificial intelligence approaches, deep learning methodologies, and epidemiological simulations for infectious disease analysis and applied scientific computation.[2]

Keywords

Mathematics, infectious disease modeling, fractional differential equations, computational epidemiology, artificial intelligence, deep learning, neural networks, stochastic systems, nonlinear dynamics, numerical simulations.

Introduction

Muhammad Farhan has contributed to interdisciplinary mathematical research involving infectious disease transmission systems, computational analysis, and artificial intelligence-assisted scientific modeling. His studies integrate theoretical mathematics with numerical computation to investigate epidemiological behavior, stability analysis, and real-world disease dynamics using advanced computational frameworks.[3]

Research Profile

Farhan completed his doctoral studies in mathematics at Abdul Wali Khan University in 2024 following earlier graduate and undergraduate training in mathematical sciences. His academic specialization focuses on infectious disease dynamics, integer-order and fractional-order systems, neural computational frameworks, and data-driven epidemiological analysis.[1]

His professional experience includes research and teaching activities at Yangzhou University, Abdul Wali Khan University, and ANSI Institute of Management Sciences. These roles involved scientific research, mathematical instruction, computational modeling, and collaborative academic work in applied mathematics and engineering-related studies.[2]

Research Contributions

  • Development of mathematical models integrating fractional-order differential equations with disease-informed neural network methodologies for epidemiological analysis.
  • Application of artificial intelligence and deep learning techniques to infectious disease prediction, stability analysis, and nonlinear computational systems.
  • Research on computational frameworks for analyzing Chikungunya virus, Hepatitis B dynamics, cancer chemotherapy systems, and epidemic transmission structures.
  • Contribution to numerical simulation methods and data-driven mathematical approaches supporting modern computational epidemiology research.

Publications

Muhammad Farhan has published research on infectious disease modeling, neural network computation, fractional differential systems, and artificial intelligence-assisted epidemiological analysis. His studies in Results in Engineering, Computational Biology and Chemistry, and related journals examine nonlinear dynamics, deep learning frameworks, and mathematical simulations for complex biomedical and computational applications.[1] [2]

  • Farhan, M., Ling, Z., Ullah, S., Riaz, M.B., and Khan, M. “Advancing nonlinear dynamics of coffee berry disease through robust dual-network framework: Deep learning and random projection neural networks.” Results in Engineering. DOI: https://doi.org/10.1016/j.rineng.2026.110184
  • Farhan, M., Waseem, Thaljaoui, A., and Rahman, M. “Data-driven investigation of an epidemic model under saturated incidence rate using deep neural networks.” Journal of Applied Mathematics and Computing. https://link.springer.com/article/10.1007/s12190-025-02639-1
  • Farhan, M., Ling, Z., Ding, J., Shah, Z., and Dobrotă, R.D. “A novel fractional computational neural framework for analyzing cancer model under chemotherapy drug.” Computer Methods in Biomechanics and Biomedical Engineering. DOI: https://doi.org/10.1080/10255842.2025.2508227
  • Farhan, M., Ling, Z., Ullah, S., Mostafa, A.M., and AlQahtani, S.A. “A novel intelligent framework for assessing within-host transmission dynamics of Chikungunya virus using an unsupervised stochastic neural network approach.” Computational Biology and Chemistry. DOI: https://doi.org/10.1016/j.compbiolchem.2025.108380
  • Farhan, M., Ling, Z., Shah, Z., Islam, S., Alshehri, M.H., and Antonescu, E. “A multi-layer neural network approach for the stability analysis of the Hepatitis B model.” Computational Biology and Chemistry. DOI: https://doi.org/10.1016/j.compbiolchem.2024.108256

Research Impact

The research profile of Muhammad Farhan reflects active scholarly participation in computational mathematics, epidemiological modeling, and artificial intelligence applications. His Scopus metrics indicate consistent publication activity and citation performance within applied mathematical sciences and interdisciplinary computational research domains.[1]

Award Suitability

Muhammad Farhan’s academic profile demonstrates sustained engagement in mathematical research, scientific publication, computational innovation, and interdisciplinary collaboration. His contributions to infectious disease modeling and artificial intelligence-assisted mathematical analysis align with evaluation criteria commonly associated with academic recognition programs and research excellence initiatives.[2]

Conclusion

Muhammad Farhan has established a research profile centered on computational mathematics, infectious disease systems, and artificial intelligence methodologies. His scholarly publications, academic training, and interdisciplinary scientific activities contribute to ongoing developments in mathematical epidemiology and computational research applications.[3]

References

  1. Elsevier. (n.d.). Scopus author details: Muhammad Farhan, Author ID 59432913900. Scopus. https://www.scopus.com/authid/detail.uri?authorId=59432913900
  2. ORCID. (n.d.). Muhammad Farhan researcher profile and academic activities. https://orcid.org/0000-0002-2235-0015
  3. Farhan, M., Ling, Z., Shah, Z., Islam, S., Alshehri, M.H., and Antonescu, E. “A multi-layer neural network approach for the stability analysis of the Hepatitis B model.” Computational Biology and Chemistry. https://doi.org/10.1016/j.compbiolchem.2024.108256
  4. Farhan, M., Ling, Z., Ullah, S., Mostafa, A.M., and AlQahtani, S.A. “A novel intelligent framework for assessing within-host transmission dynamics of Chikungunya virus using an unsupervised stochastic neural network approach.” Computational Biology and Chemistry. https://doi.org/10.1016/j.compbiolchem.2025.108380
  5. Farhan, M., Ling, Z., Ullah, S., Riaz, M.B., and Khan, M. “Advancing nonlinear dynamics of coffee berry disease through robust dual-network framework: Deep learning and random projection neural networks.” Results in Engineering. https://doi.org/10.1016/j.rineng.2026.110184