Suleyman Cetinkaya | Mathematics | Best Researcher Award

Assist. Prof. Dr. Suleyman Cetinkaya | Mathematics | Best Researcher Award

AssistProfDr. at Department of Mathematics from Kocaeli University, Turkey

Asst. Prof. Süleyman Çetinkaya is a distinguished academic in the Department of Mathematics at Kocaeli University’s Faculty of Arts and Sciences. His research primarily focuses on applied mathematics, with a particular emphasis on fractional calculus and its applications in solving complex differential equations. Throughout his career, Dr. Çetinkaya has contributed significantly to the field, authoring numerous publications and presenting his findings at various international conferences.

Professional Profile​

Education

Dr. Çetinkaya completed his undergraduate studies in 1987 at Istanbul University’s Faculty of Literature, majoring in German Language and Literature. He further pursued a master’s degree at Istanbul University’s Faculty of Economics, focusing on the socio-cultural structure of the European Union. His thesis, titled “Environmental Policy in Local Governments During the EU Accession Process,” reflects his interdisciplinary approach, integrating environmental concerns with socio-economic studies.

Professional Experience

Beginning his career in 1993 at Tuzla Municipality, Dr. Çetinkaya held multiple roles, including Director of Private Office, Account Affairs, Environmental Protection and Cleaning Affairs, Health Affairs, and Foreign Relations. In 2010, he transitioned to academia, joining Kocaeli University as a Research Assistant. His diverse professional background enriches his teaching and research, providing students with real-world insights into the applications of mathematics in various sectors.

Research Interests

Dr. Çetinkaya’s research interests lie in applied mathematics, specifically fractional calculus. He explores the solutions of fractional differential equations and their applications in modeling real-world phenomena. His work aims to bridge the gap between theoretical mathematics and practical applications, contributing to advancements in engineering and technology.

Research Skills

With expertise in fractional calculus, Dr. Çetinkaya employs analytical and numerical methods to tackle complex mathematical problems. His proficiency in developing and applying mathematical models enables him to address challenges in various scientific and engineering domains. Additionally, his interdisciplinary background allows him to integrate concepts from different fields, enhancing the depth and applicability of his research.

Awards and Honors

Dr. Çetinkaya’s contributions to mathematics have been recognized through various accolades. He has an H-index of 4 in Web of Science and 2 in Scopus, reflecting the impact and quality of his research. His publications have garnered numerous citations, underscoring his influence in the academic community.

Conclusion

Asst. Prof. Süleyman Çetinkaya exemplifies dedication to both academic excellence and practical application of mathematical principles. His interdisciplinary education and diverse professional experience enrich his research and teaching methodologies. By focusing on fractional calculus and its real-world applications, Dr. Çetinkaya continues to contribute significantly to the advancement of applied mathematics, inspiring both his peers and students.

Publications Top Notes​

  • Title: A New Approach for the Fractional Rosenau–Hyman Problem by ARA Transform
    Authors: Suleyman Cetinkaya; Ali Demir
    Year: 2025

  • Title: The Effect of New Integral Transform on the Establishment of Solutions for Fractional Mathematical Models
    Authors: Suleyman Cetinkaya; Ali Demir; Hulya Kodal Sevindir
    Year: 2024

  • Title: On the Solution of Mathematical Model Including Space-Time Fractional Diffusion Equation in Conformable Derivative, Via Weighted Inner Product
    Authors: Süleyman Çetinkaya; Ali Demir
    Year: 2023

  • Title: The Analytic Solution of the Fractional Rosenau–Hyman Model in Liouville-Caputo Sense
    Authors: Suleyman Cetinkaya; Ali Demir
    Year: 2023

  • Title: Time Fractional Problem via Inner Product Including Weighted Function
    Authors: Süleyman Çetinkaya; Ali Demir
    Year: 2022

  • Title: On Effects of a New Method for Fractional Initial Value Problems
    Authors: Hülya Kodal Sevindir; Süleyman Çetinkaya; Ali Demir; Zengtao Chen
    Year: 2021

  • Title: Analysis of Fractional Fokker-Planck Equation with Caputo and Caputo-Fabrizio Derivatives
    Authors: Suleyman Cetinkaya; Ali Demir; Dumitru Baleanu
    Year: 2021

  • Title: Solution of Space-Time-Fractional Problem by Shehu Variational Iteration Method
    Authors: Suleyman Cetinkaya; Ali Demir; Hulya Kodal Sevindir; Marianna Ruggieri
    Year: 2021

  • Title: Time Fractional Equation with Non-homogenous Dirichlet Boundary Conditions
    Authors: Süleyman Çetinkaya; Ali Demir
    Year: 2020

  • Title: Equation Including Local Fractional Derivative and Neumann Boundary Conditions
    Authors: Süleyman Çetinkaya; Ali Demir
    Year: 2020

  • Title: The Analytic Solution of Time-Space Fractional Diffusion Equation via New Inner Product with Weighted Function
    Authors: Süleyman Çetinkaya; Ali Demir
    Year: 2019

  • Title: Asymptotic Analysis of Shearlet Transform for Inpainting
    Authors: Hülya Kodal Sevindir; Cüneyt Yazıcı; Süleyman Çetinkaya
    Year: 2018

 

Nitiraj V. Kulkarni | Mathematics | Young Scientist Award

Mr. Nitiraj Kulkarni | Mathematics | Young Scientist Award

Student Researcher at Vishwakarma University, Pune, India

Nitiraj V. Kulkarni is an aspiring researcher currently pursuing a Bachelor of Technology (B.Tech.) in Artificial Intelligence and Data Science at Vishwakarma University, Pune. His academic and research contributions span across multiple disciplines, including Computational Fluid Mechanics, Artificial Neural Networks (ANN), and Data Science. He has co-authored the Handbook for Basics of Artificial Intelligence and has published 10 research papers in reputed journals indexed in SCI and Scopus. Nitiraj has also made a significant impact by publishing over 12,000 datasets on various platforms, contributing valuable resources to the research community. Beyond academia, he has applied his technical skills to cybersecurity, receiving a letter of appreciation from the Director General of MSRTC for identifying a critical system vulnerability. Additionally, he has authored 8 books and has a patent under review, showcasing his dedication to knowledge dissemination and innovation. With his multidisciplinary approach, Nitiraj is making remarkable strides in integrating AI with engineering applications.

Professional Profile

Education

Nitiraj V. Kulkarni is pursuing his Bachelor of Technology (B.Tech.) in Artificial Intelligence and Data Science at Vishwakarma University, Pune. His academic background is centered around Machine Learning, Neural Networks, Computational Mathematics, and Data Science, providing a strong theoretical foundation in AI and its real-world applications. He has actively engaged in research-driven learning, with a focus on Artificial Neural Networks (ANN) in Fluid Mechanics. His education extends beyond formal coursework, as he has participated in research projects, self-learning, and collaborative work with leading scientists like Dr. Jagadish V. Tawade. Through these experiences, he has gained proficiency in computational modeling, numerical simulations, and AI-driven predictive analytics. His commitment to education is evident in his scientific publications and books, which contribute to knowledge dissemination in AI and engineering. Nitiraj’s strong academic foundation, combined with practical research exposure, positions him as a promising young scientist with significant contributions to AI and computational sciences.

Professional Experience

Despite being an undergraduate student, Nitiraj V. Kulkarni has built an impressive professional profile through active research, collaborations, and industry engagement. His most notable achievement includes receiving a letter of appreciation from the Director General of MSRTC (Government of Maharashtra) for identifying a critical system vulnerability, showcasing his expertise in cybersecurity and system analysis. He has also worked on an advanced research project involving Artificial Neural Networks (ANN) for Unsteady Boundary Layer Flow and Heat Transfer, demonstrating his ability to integrate AI with engineering and physics. In addition, Nitiraj has published 10 research papers in SCI and Scopus-indexed journals, authored 8 books, and has a patent under review, highlighting his contributions to innovation and knowledge dissemination. He has also actively collaborated with senior researchers like Dr. Jagadish V. Tawade, further strengthening his research capabilities. His multidisciplinary expertise reflects his commitment to bridging AI with computational mechanics and industry applications.

Research Interests

Nitiraj V. Kulkarni’s research interests are deeply rooted in the fields of Artificial Intelligence, Computational Fluid Mechanics, and Data Science. His primary focus lies in applying Artificial Neural Networks (ANN) to Fluid Mechanics for solving complex engineering problems, including boundary layer flow, heat transfer analysis, and thermoelectric energy harvesting. Additionally, he is interested in Machine Learning and Data Science, where he develops AI-driven predictive models and analyzes large-scale datasets to extract meaningful insights. His research extends into cybersecurity, where he explores system vulnerabilities and AI-based security solutions, as demonstrated by his work with MSRTC. Nitiraj is also engaged in nanofluid heat transfer studies, contributing to advancements in thermal energy management. His diverse research interests highlight his multidisciplinary approach, allowing him to tackle complex engineering challenges using AI and computational techniques. His work is aimed at developing innovative, data-driven solutions for real-world applications in engineering and technology.

Research Skills

Nitiraj V. Kulkarni possesses a diverse and advanced set of research skills, making him a valuable contributor to multiple scientific disciplines. His expertise in Artificial Neural Networks (ANN) allows him to develop AI-driven models for fluid mechanics and thermal engineering. He is highly proficient in Computational Fluid Dynamics (CFD), numerical modeling, and predictive analytics, which he applies in solving complex engineering problems. His data analysis and machine learning skills enable him to handle large-scale datasets and optimize predictive models for various applications. Additionally, his scientific writing and publishing experience is evident from his 10+ research papers and 8 books, contributing significantly to AI and computational sciences. Nitiraj also has strong skills in cybersecurity and vulnerability assessment, as demonstrated by his MSRTC recognition. His combination of theoretical knowledge, computational proficiency, and real-world application skills makes him a promising young scientist in AI and engineering research.

Awards and Honors

Nitiraj V. Kulkarni has received multiple recognitions for his contributions to AI, computational research, and cybersecurity. One of his most significant honors is the letter of appreciation from the Director General of MSRTC (Government of Maharashtra) for identifying a critical system vulnerability, highlighting his cybersecurity expertise. He has also published 10+ research papers in prestigious SCI and Scopus-indexed journals, demonstrating his strong academic research impact. His contributions to education and knowledge dissemination are reflected in his 8 books on AI, computational techniques, and scientific research. Additionally, he has published over 12,000 datasets, significantly aiding the research community in data-driven studies. Nitiraj has also collaborated with renowned scientists like Dr. Jagadish V. Tawade and has a patent under review, showcasing his innovation potential. His recognitions reflect his dedication to AI, cybersecurity, computational mechanics, and scientific research, positioning him as a strong candidate for the Young Scientist Award.

Conclusion

Nitiraj V. Kulkarni is an exceptional young researcher with a strong foundation in Artificial Intelligence, Data Science, and Computational Fluid Mechanics. His contributions to scientific research, cybersecurity, and AI-driven engineering solutions set him apart as an emerging leader in these fields. Through 10+ research papers, 8 books, a patent application, and over 12,000 datasets, he has demonstrated an impressive commitment to knowledge dissemination and innovation. His research has practical applications, as seen in his MSRTC cybersecurity recognition, proving his ability to solve real-world technological challenges. Nitiraj’s ability to integrate AI with computational mechanics, cybersecurity, and industry applications showcases his multidisciplinary expertise. With continued research, global collaborations, and industry engagement, he has the potential to make groundbreaking contributions to AI, fluid mechanics, and engineering applications. His achievements and dedication to innovation make him a deserving candidate for the Young Scientist Award, and a future leader in scientific research.

Publications Top Notes

  1. Effect of Williamson Nanofluid Across an Exponentially Stretched Sheet with Chemical Reaction Under the Influence of Joules Heating
    S. Swami, S. Biradar, J.V. Tawade, N.V. Kulkarni, F. Yuldashev, M. Gupta, …
    2025

  2. Thermo-fluid dynamics of non-Newtonian Casson fluid in expanding-contracting channels with Joule heating and variable thermal properties
    S. Rafiq, B.A. Bilal, A. Afzal, J.V. Tawade, N.V. Kulkarni, B. Abdullaeva, …
    2025

  3. Numerical solutions for unsteady laminar boundary layer flow and heat transfer over a horizontal sheet with radiation and nonuniform heat source/sink
    M. Diwate, J.V. Tawade, P.G. Janthe, M. Garayev, M. El-Meligy, N. Kulkarni, …
    2024

  4. Heat transfer mechanism for Newtonian and non-Newtonian Casson hybrid nanofluid subject to thermophoresis and Brownian motion over a movable wedge surface
    S. Swami, S. Biradar, M.Q. Gubari, S.P. Samrat, J.V. Tawade, N. Kulkarni, …
    2025

  5. Thermoelectric energy harvesting from geothermal micro-seepage
    N. Kulkarni, M. Al-Dossari, J. Tawade, A. Alqahtani, M.I. Khan, B. Abdullaeva, …
    2024

  6. Soret and nonuniform heat source/sink effects in micropolar nanofluid flow over an inclined stretching sheet
    M. Diwate, P.G. Janthe, N. Kulkarni, S. Sunitha, J.V. Tawade, N. Nazarova, …
    2025

  7. Optimizing nanoparticle dispersion and heat transfer in Williamson nanofluids under magnetic influence
    S. Swami, S. Biradar, J.V. Tawade, N.V. Kulkarni, B.S. Abdullaeva, D.M. Khidhir, …
    2025

  8. Optimizing Ibrutinib bioavailability: Formulation and assessment of hydroxypropyl-β-cyclodextrin-based nanosponge delivery systems
    S. Sampathi, N. Kulkarni, D. Bhikshapathi, J.V. Tawade, N. Tarakaramu, …
    2025

  9. Thermal and solutal performance analysis featuring fully developed chemically reacting micro-rotational convective flow in an open-ended vertical channel
    G.T. Gitte, S. Kalyan, H. Saraswathi, V. Kulkarni, M. Jameel, J.V. Tawade, …
    2025

  10. Effects of exponentially stretching sheet for MHD Williamson nanofluid with chemical reaction and thermal radiative
    S.P. Pallavi, M.B. Veena, J.V. Tawade, N. Kulkarni, S.U. Khan, M. Waqas, …
    2024