Prof. Dr. Rômulo Santos | Applied Mathematics | Best Academic Researcher Award

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Prof. Dr. Rômulo Santos | Applied Mathematics | Best Academic Researcher Award

Postdoctoral Researcher at Santa Cruz State University, Ilhéus, Bahia, Brazil

Dr. Rômulo Damasclin C. Santos 🇧🇷 is an accomplished applied mathematician and fluid dynamics specialist whose career bridges deep theoretical insight with computational precision. With a Ph.D. in Applied Mathematics from the University of Porto 🎓 and postdoctoral research at the prestigious Instituto Tecnológico de Aeronáutica (ITA) 🔬, he seamlessly integrates mathematical rigor with practical modeling. His passion lies in deciphering real-world physical phenomena using tools such as Partial and Integro-Differential Equations, Complex Analysis, and Fluid Dynamics 💨. He has held diverse teaching and research roles across Brazil, including UESC and UEMS, contributing significantly to academic development nationwide 📘. A published innovator, Dr. Santos has developed original computational methods like HODIM and Hybrid Adaptive DRM, alongside expertise in C++, Python, and MATLAB 💻. Actively involved in peer-review and editorial duties, his interdisciplinary approach is anchored in innovation, collaboration, and mathematical excellence. 🧠🌐

Professional Profile 

🎓 Education

Dr. Santos’s educational path reflects an unyielding drive for mastery in applied mathematics and engineering. He earned his Ph.D. in Applied Mathematics from the University of Porto (Portugal) in 2018, focusing on fluid dynamics through advanced numerical and analytical models 📘. Prior to that, he completed an M.Sc. in Mechanical Engineering at the Federal University of Itajubá (UNIFEI), specializing in flow machines and thermofluid systems 🌪️. His academic journey began with a Bachelor’s degree in Mathematics at the Federal University of Acre (UFAC), where he concurrently explored fractal geometry and object-oriented programming 🧮💻. Currently, he is further expanding his scientific breadth through postdoctoral research in Physics at ITA, one of Brazil’s foremost institutions in science and technology 🔬. This multifaceted academic background underpins his ability to approach problems from both abstract and applied angles.

👨‍🏫 Professional Experience

Dr. Santos has amassed a wealth of academic and research experience across Brazil’s most respected institutions 🏛️. He currently serves as a Postdoctoral Research Fellow at UESC and concurrently holds a professorship in Mathematics at UEMS, demonstrating his dual commitment to research and education 📚. His past roles include teaching positions at Federal Institutes (Santa Catarina, Acre), Mato Grosso State University, and UVERSO University Center, often within the engineering or mathematics departments 🧠. Whether substituting or leading research, he brought clarity and innovation to diverse academic environments. With more than a decade of academic engagement, he has nurtured student talent, advanced new methodologies, and contributed to institutional development nationwide. His dynamic roles—spanning from mathematical modeling to engineering theory—reflect a professional identity grounded in flexibility, excellence, and forward-thinking mentorship. 🎓🧪

🔬 Research Interests

Dr. Santos’s research is a fusion of theoretical depth and computational elegance 🧬. His core interests revolve around Fluid Dynamics, Turbulence Modeling, and Heat Transfer, particularly in incompressible Newtonian fluids 🌊. His toolkit includes advanced methods like Immersed Boundary Method (IBM), Smoothed-Particle Hydrodynamics (SPH), and LES, all tailored to simulate real-world chaotic flows. He integrates Partial, Integral, and Integro-Differential Equations to decipher the complex interplay in dynamical systems 🔁. Using programming languages such as C++, Python, and MATLAB, he develops original algorithms, including the High-Order Dynamic Integration Method (HODIM) and Hybrid Adaptive DRM for large-scale systems 🖥️. His mathematical framework draws from Complex Analysis, Functional Analysis, and Numerical Methods, making his contributions valuable across engineering, physics, and applied mathematics domains. His ambition is to model nature’s complexities through computation and logic, offering insights that cross traditional disciplinary boundaries. 🔗🌌

🏅 Awards and Honors

Dr. Santos has earned national and international recognition through prestigious academic engagements and editorial responsibilities 🌍. His Ph.D., validated in Brazil by UFRGS, exemplifies international academic excellence 🎓. As a reviewer and editorial board member for several renowned journals—such as Journal of Applied Fluid Mechanics, Brazilian Journal of Physics, and ASTES Journal—he contributes to the global dissemination of scientific knowledge 📖. Moreover, his commitment to innovation is officially recognized through computer program registrations with INPI, Brazil’s national patent authority 🏷️. He is a respected member of elite professional bodies, including the Brazilian Society for Applied and Computational Mathematics (SBMAC), Brazilian Mathematical Society (SBM), and the International Association of Engineers and Computer Scientists (IAENG) 🤝. These affiliations, coupled with his published innovations, affirm his role as a forward-thinking thought leader in applied mathematics and engineering systems.

📚 Publications Top Note 

1. Hypermodular Neural Operators: Ramanujan-Kantorovich Synthesis in Sobolev Approximation Theory

  • Authors: Rômulo D. C. dos Santos & Jorge H. de Oliveira Sales

  • Year: 2025 (July 8)

  • Source: HAL Open Science (Preprint)

  • Citation: HAL ID: hal-05115451

  • Summary: This work proposes a fusion of Ramanujan summability concepts with Kantorovich-type neural operators to form “hypermodular” neural frameworks. It operates within Sobolev spaces and demonstrates superior convergence and approximation behavior, especially near boundaries. The authors establish convergence results and operator stability using Sobolev norms.

2. Symmetrized Neural Network Operators in Fractional Calculus: Caputo Derivatives, Asymptotic Analysis, and the Voronovskaya–Santos–Sales Theorem

  • Authors: Rômulo D. C. dos Santos, Jorge H. de Oliveira Sales, Gislan S. Santos

  • Year: 2025 (June 30)

  • Source: Axioms (MDPI), Journal Article

  • DOI: 10.3390/axioms14070510

  • Summary: This article introduces symmetrized neural network operators tailored to fractional calculus and Caputo derivatives. It develops a new asymptotic theorem named after the authors, offering enhanced convergence analysis for fractional neural networks. Applications include fractional signal processing and modeling of dissipative systems.

3. Innovations in Neural Approximation: Uniting Symmetrized Kantorovich-Ramanujan Operators within Sobolev Spaces

  • Authors: Rômulo D. C. dos Santos & Jorge H. de Oliveira Sales

  • Year: 2025 (June 23)

  • Source: HAL Open Science (Preprint)

  • Citation: HAL ID: hal-05115451 (version 1)

  • Summary: A foundational version of the unified Kantorovich-Ramanujan operator framework for neural networks. This work extends approximation theory in Sobolev spaces using Ramanujan-style summability corrections and operator symmetrization.

4. Advancing Neural Approximation: The Role of Kantorovich-Ramanujan-Santos-Sales Operators in Modern Computation

  • Authors: Rômulo D. C. dos Santos & Jorge H. de Oliveira Sales

  • Year: 2025 (May 26)

  • Source: Zenodo (CERN), Preprint

  • DOI: 10.5281/ZENODO.15514812

  • Summary: Introduces a new family of operators combining Kantorovich-Ramanujan theory with neural networks, emphasizing boundary regularization, smoothness control, and numerical stability. A Voronovskaya-type expansion is derived for these operators.

5. Stochastic Fractional Neural Operators: A Symmetrized Approach to Modeling Turbulence in Complex Fluid Dynamics

  • Authors: Rômulo D. C. dos Santos & Jorge H. de Oliveira Sales

  • Year: 2025 (May 21)

  • Source: arXiv (Computer Science > Machine Learning)

  • DOI: 10.48550/ARXIV.2505.14700

  • Summary: This paper explores stochastic extensions of fractional neural operators applied to fluid turbulence. By incorporating symmetrized neural kernels and stochastic perturbations, the authors model uncertainty and chaotic behavior in turbulent flow systems.

6. Anomalous Gradients in AI: Multivariate Fractional Calculus Unifying Landau Inequalities and Deep Operator Stability

  • Author: Rômulo D. C. dos Santos

  • Year: 2025 (May 18)

  • Source: Zenodo (CERN), Preprint

  • DOI: 10.5281/ZENODO.15454789

  • Summary: Investigates the connection between multivariate fractional calculus and gradient stability in AI. The study proposes a new operator framework addressing anomalous gradients through generalizations of Landau inequalities.

7. Extension of Symmetrized Neural Network Operators with Fractional and Mixed Activation Functions

  • Authors: Rômulo D. C. dos Santos & Jorge H. de Oliveira Sales

  • Year: 2025 (May 11)

  • Source: The Journal of Engineering and Exact Sciences

  • DOI: 10.18540/jcecvl11iss1pp21662

  • Summary: This work extends neural approximation theory using fractional and mixed-type activation functions (like q-deformed and inverse polynomial activations). It presents a new Jackson-type inequality and convergence analysis.

8. Neural Network Operators for the New Era of Fractional Calculus: Bridging Analysis and Artificial Intelligence Systems

  • Author: Rômulo D. C. dos Santos

  • Year: 2025 (April 6)

  • Source: Zenodo (CERN), Preprint

  • DOI: 10.5281/ZENODO.15163347

  • Summary: Introduces neural operators that operate natively in the fractional calculus domain. Sets a foundational framework unifying AI learning mechanisms with fractional integral and differential operators.

9. Beyond Traditional Approximation: Advanced Voronovskaya-Damasclin Theory for Neural Network Approximation in Fractional Calculus

  • Author: Rômulo D. C. dos Santos

  • Year: 2025 (March 30)

  • Source: Zenodo (CERN), Preprint

  • DOI: 10.5281/ZENODO.15109088

  • Summary: Provides theoretical extensions of Voronovskaya’s theorem into the realm of neural approximation using fractional operators. Establishes sharp asymptotic error bounds for fractional neural network functionals.

10. Bifurcations, Stability and Numerical Analysis of Turbulent Flow (Bidimensional)

  • Author: Rômulo D. C. dos Santos

  • Year: 2025 (April 17)

  • Source: Observatório de la Economía Latinoamericana

  • DOI: 10.55905/oelv23n4-125

  • Summary: Focuses on the use of fractional and numerical methods to model bifurcation behavior in two-dimensional turbulent flows. Combines theory from dynamical systems with neural-based numerical solvers.

🧩 Conclusion

Dr. Rômulo Damasclin C. Santos is a polymath in the truest sense—merging theory, simulation, and real-world application into a cohesive scientific narrative 🔄. His journey from the Amazon to Europe and back to Brazil’s top academic circles reflects determination, intellectual courage, and innovation 🌎. As an educator, he has shaped minds across Brazil; as a researcher, he has expanded the boundaries of what’s possible in fluid dynamics and numerical modeling 💡. His multidisciplinary mindset enables him to tackle complex problems with originality, backed by robust mathematical foundations and computational fluency. In a world increasingly driven by scientific modeling and simulation, Dr. Santos stands out as a pioneering figure ready to lead the charge in engineering mathematics and technological advancement 🚀📊.

Jeongho Ahn | Applied Mathematics | Best Researcher Award

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Dr. Jeongho Ahn | Applied Mathematics | Best Researcher Award

Full Professor at Arkansas State University, United States

Dr. Jeongho Ahn is a full professor in the Department of Mathematics and Statistics at Arkansas State University (ASU) since Fall 2021. He has been part of ASU since 2008, serving in various roles, including associate and assistant professor. Dr. Ahn earned his Ph.D. in Mathematics from The University of Iowa in 2003. His research focuses on applied mathematics, numerical analysis, partial differential equations, and dynamic contact problems. He is known for his work on finite element methods and complementarity problems. Dr. Ahn is dedicated to teaching and research with a strong commitment to the advancement of mathematics. 📚🧑‍🏫🔢

Professional Profile:

Orcid

Scopus

Education and Experience

  • Ph.D. in Mathematics from The University of Iowa, USA (2003) 🎓

  • M.S. in Mathematics from Kyung Hee University, South Korea (1991) 🇰🇷

  • B.S. in Mathematics from Kyung Hee University, South Korea (1989) 🇰🇷

Teaching Experience:

  • Full Professor, Department of Mathematics and Statistics, ASU (2021–Present) 📚

  • Associate Professor, ASU (2015–2021) 🧑‍🏫

  • Assistant Professor, ASU (2009–2015) 🔢

  • Visiting Assistant Professor, ASU (2008–2009) 🌍

Professional Development 

Dr. Jeongho Ahn has continuously advanced his academic and professional career, establishing himself as a leader in applied mathematics. With years of experience, his teaching spans topics such as algebra, calculus, differential equations, and numerical analysis. He has worked extensively on research in dynamic contact problems and finite element methods, significantly contributing to the development of mathematical theories. Dr. Ahn remains engaged in further professional development through his active research in numerical methods, participating in conferences and workshops to share insights and innovations in applied mathematics. His work fosters collaboration in mathematical and engineering fields. 🏫🔬👨‍🔬

Research Focus 

Dr. Jeongho Ahn’s research primarily revolves around applied mathematics, where he explores numerical analysis, partial differential equations (PDEs), and dynamic contact problems. His expertise includes the development of finite element methods used to solve complex equations in various applications. He works on complementarity problems and differential variational inequalities, addressing real-world challenges in engineering, physics, and economics. By advancing computational techniques, Dr. Ahn aims to improve mathematical models in diverse fields, making significant strides in mathematical modeling and problem-solving methodologies that have broad implications in science and technology. 📊⚙️💻🧮

Awards and Honors

  • Full Professor, Department of Mathematics and Statistics, ASU (2021–Present) 🏅

  • Associate Professor, ASU (2015–2021) 🌟

  • Assistant Professor, ASU (2009–2015) 🎓

Publication Top Notes

  • Detachment Waves in Frictional Contact: Analysis and Simulations of a Two-Mass System

    • Citation: Ahn, J. (2024). Detachment waves in frictional contact: analysis and simulations of a two-mass system. Nonsmooth Problems with Publications in Mathematics, Banach Center Publications.

    • Year: 2024

    • Details: This paper likely explores detachment waves in frictional contact between two masses. It may involve the modeling and simulation of how one mass separates from another due to dynamic forces and friction.

  • A Generalized Duffing Equation with the Coulomb’s Friction Law and Signorini-Type Contact Conditions

    • Citation: Ahn, J. (2023). A generalized Duffing equation with the Coulomb’s friction law and Signorini-type contact conditions. Nonlinear Analysis: Real World Applications.

    • Year: 2023

    • Details: This paper generalizes the Duffing oscillator equation by including Coulomb friction and Signorini contact conditions, both of which introduce nonsmooth behaviors into the system. It explores how these factors influence nonlinear oscillations and stability.

  • A Spring-Beam System with Signorini’s Condition and the Normal Compliance Condition

    • Citation: Ahn, J. (2023). A spring-beam system with Signorini’s condition and the normal compliance condition. International Journal of Numerical Analysis and Modeling.

    • Year: 2023

    • Details: This study investigates a spring-beam system under Signorini’s non-penetration condition and normal compliance, examining how these boundary conditions affect the system’s deformation and response to applied forces.

  • Nonlinear Thermoviscoelastic Timoshenko Beams with Dynamic Frictional Contact

    • Citation: Ahn, J. (2022). Nonlinear thermoviscoelastic Timoshenko beams with dynamic frictional contact. Applied Analysis.

    • Year: 2022

    • Details: The paper addresses Timoshenko beams that exhibit nonlinear thermoviscoelastic behavior and experience dynamic frictional contact. The study likely combines thermal, mechanical, and viscoelastic effects to model beam deformations under various dynamic conditions.

  • A Rod-Beam System with Dynamic Contact and Thermal Exchange Condition

    • Citation: Ahn, J. (2021). A rod-beam system with dynamic contact and thermal exchange condition. Applied Mathematics and Computation.

    • Year: 2021

    • Details: This paper discusses the interaction between a rod and a beam, incorporating dynamic contact and thermal exchange conditions. The study likely explores how thermal effects influence the mechanical response of the system when subject to contact forces.

Conclusion 

Dr. Jeongho Ahn’s career is defined by a remarkable blend of academic leadership, cutting-edge research, and teaching excellence. His work in numerical methods, finite element analysis, and applied mathematics has had a broad impact across multiple domains, including engineering, materials science, and economics. He is not only advancing mathematical theory but also developing practical tools that are shaping the future of these fields.

Given his long-standing academic contributions, innovative research, and commitment to excellence in education, Dr. Jeongho Ahn is exceptionally well-qualified for the Best Researcher Award. His work continues to influence both the academic world and the practical, real-world application of mathematical methods, marking him as a leading figure in his field.

Fairouz Tchier | Applied Mathematics | Best Researcher Award

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Prof Dr. Fairouz Tchier | Applied Mathematics | Best Researcher Award 

Scopus Profile

Educational Details:

Prof. Fairouz Tchier earned her Ph.D. in Mathematics with a focus on theoretical computer science from Université Laval, Quebec City, in 1996. She completed her Master of Science in Mathematics (specializing in functional analysis) from Université de Sherbrooke in 1990, and her Bachelor’s degree in Mathematics (functional analysis) from Université de Sétif, Algeria, in 1986.

Professional Experience

Prof. Tchier is currently a Full Professor at the Mathematics Department at King Saud University, a position she has held since 2017. She has been with the university since 1996, progressing from Assistant Professor to Associate Professor in 2008. With a career spanning more than two decades, she has taught numerous courses in pure and applied mathematics as well as theoretical computer science. She has also supervised student projects and is deeply involved in the management of e-courses.

In addition to her teaching responsibilities, she is a recognized leader in quality assurance and accreditation, serving as a Certified Learning Quality Manager and an active member in the accreditation process for King Saud University. She has held various administrative and coordinating roles in accreditation and program evaluation.

Research Interest

Her research interests focus on mathematics and theoretical computer science. She is highly regarded for her work, being ranked among the top 2% of researchers most cited for their contributions to mathematics in 2020 according to the Scopus database.

Awards & Recognitions

Throughout her career, Prof. Tchier has been recognized for her academic excellence and teaching. She has received awards such as the Academic Excellence Award at the Women’s Higher Education Symposium and the Best Staff in Teaching Award at the Mathematics Department at King Saud University. She has also been the recipient of national and international scholarships, including from NSERC (Canada).

Top Notable Publications

“Boundary values of Hankel and Toeplitz determinants for q-convex functions”

Authors: Hadi, S.H., Shaba, T.G., Madhi, Z.S., Lupaş, A.A., Tchier, F.

Published in: MethodsX, 2024, Vol. 13, Article 102842

Citations: 0

“Exploring expected values of topological indices of random cyclodecane chains for chemical insights”

Authors: Chunsong, B., Naeem, A., Yousaf, S., Tchier, F., Issa, A.

Published in: Scientific Reports, 2024, Vol. 14(1), Article 10065

Citations: 1

“The fractional analysis of thermo-elasticity coupled systems with non-linear and singular nature”

Authors: Rab, A., Khan, S., Khan, H., Tawfiq, F., Nadeem, M.

Published in: Scientific Reports, 2024, Vol. 14(1), Article 9663

Citations: 0

“Sharp coefficient inequalities of starlike functions connected with secant hyperbolic function”

Authors: Raza, M., Bano, K., Xin, Q., Tchier, F., Malik, S.N.

Published in: Journal of Inequalities and Applications, 2024, Vol. 2024(1), Article 56

Citations: 0

“Computation of expected values of some connectivity based topological descriptors of random cyclooctane chains”

Authors: Yousaf, S., Iqbal, Z., Tariq, S., Tchier, F., Issa, A.

Published in: Scientific Reports, 2024, Vol. 14(1), Article 7713

Citations: 0

“Analysis of two layered peristaltic-ciliary transport of Jeffrey fluid and in vitro preimplantation embryo development”

Authors: Ashraf, H., Siddique, I., Siddiqa, A., Bhatti, S., Rehman, A.

Published in: Scientific Reports, 2024, Vol. 14(1), Article 1469

Citations: 1

“Sharp coefficient bounds for a class of symmetric starlike functions involving the balloon shape domain”

Authors: Khan, B., Gong, J., Khan, M.G., Tchier, F.

Published in: Heliyon, 2024, Vol. 10(19), Article e38838

Citations: 1

Conclusion

Given Dr. Tchier’s extensive qualifications, impressive academic background, multiple awards, long-standing work experience, and contributions to the global research community, she is a strong and deserving candidate for the Research for Best Researcher Award. Her consistent impact on the field of applied mathematics, theoretical computer science, and academic quality makes her an ideal recipient of such an honor.