Dr. Muhammad Ahsan | Mathematics | Research Excellence Award

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Dr. Muhammad Ahsan | Mathematics | Research Excellence Award

Assistant Professor | University of Swabi | Pakistan

Dr. Muhammad Ahsan is a distinguished scholar in Mathematics, recognized for his influential contributions to applied Mathematics, computational Mathematics, and numerical methods. His research spans high-order wavelet collocation techniques, multi-resolution algorithms, and advanced modeling approaches that address complex challenges in science and engineering through the rigorous application of Mathematics. As an active researcher in the global Mathematics community, he has authored more than thirty peer-reviewed publications in leading international journals, demonstrating consistent excellence in theoretical and computational Mathematics. Dr. Muhammad Ahsan has built a strong reputation for advancing innovative  methodologies in Mathematics, particularly in the areas of differential equations, inverse problems, nonlinear systems, and wavelet-based numerical frameworks. His collaborative work with researchers from multiple countries reflects his commitment to expanding the frontiers of Mathematics through interdisciplinary engagement. His impactful publications, extensive citation record, and sustained research productivity underscore the importance of his contributions to applied Mathematics and strengthen the global relevance of his work. In addition to his research achievements, he has played a pivotal role in academic leadership, contributing to institutional development, departmental responsibilities, and scholarly review activities for numerous international journals in Mathematics. His mentorship of graduate and undergraduate students further reflects his dedication to nurturing the next generation of professionals in Mathematics. Through his continuous pursuit of high-quality research, dedication to international collaboration, and commitment to advancing Mathematics, Dr. Muhammad Ahsan exemplifies scholarly excellence and global academic impact. His work remains a valuable asset to the broader scientific community, reinforcing the essential role of Mathematics in addressing modern scientific and technological challenges. Scopus profile of 591 Citations, 37 Documents, 16 h-index.

Profiles: Scopus | Google Scholar

Featured Publications

1. High-order wavelet-based numerical algorithms for nonlinear singular Lane–Emden–Fowler equations: Applications to physical models in astrophysics. (2026). Astronomy and Computing.

2. A high-order Haar wavelet approach to solve differential equations of fifth-order with simple, two-point and two-point integral conditions. (2026). Applied Numerical Mathematics.

3. Enhanced resolution in solving first-order nonlinear differential equations with integral condition: A high-order wavelet approach. (2025). European Physical Journal Special Topics.

Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

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Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

Professor | Xi'an Jiaotong University | China

Prof. Dr. Jinju Sun is a distinguished scholar in the School of Energy and Power Engineering at Xi’an Jiaotong University, renowned for her pioneering contributions to fluid mechanics, turbomachinery, and multiphase flow systems through advanced Computational Methods. Her educational journey spans cryogenic engineering to a PhD in turbomachinery and engineering mechanics, which laid the foundation for her expertise in Computational Methods applied to turbomachinery optimization, Lattice Boltzmann modeling, and Vortex Method simulations. Throughout her professional career, she has served as a researcher, lecturer, and professor, advancing research through numerous national and international collaborations emphasizing Computational Methods in fluid dynamics and green energy system design. She has received prestigious honors, including the Donald Julius Groen Prize and the Arthur Charles Main Award from the Institution of Mechanical Engineers (UK), in recognition of her outstanding achievements utilizing Computational Methods for energy system modeling and flow optimization. Her research interests include cryogenic liquid turbines, compressor instabilities, and innovative Computational Methods for fluid-structure interaction and multiphase flow behavior. She has authored numerous high-impact publications and holds multiple international patents that demonstrate her excellence in Computational Methods-based innovation. Prof. Dr. Jinju Sun’s research skills encompass CFD modeling, LBM, topology optimization, and Computational Methods-driven analysis for turbomachinery and green energy systems. In conclusion, her dedication to advancing Computational Methods in engineering has positioned her as a global leader driving innovation, sustainability, and scientific excellence in modern energy and power engineering.

Profile: ORCID

Featured Publications

1. Qu, Y., Sun, J., Song, P., & Wang, J. (2025). Enhancing efficiency and economic viability in Rectisol system with cryogenic liquid expander. Asia-Pacific Journal of Chemical Engineering.

2. Ge, Y., Peng, J., Chen, F., Liu, L., Zhang, W., Liu, W., & Sun, J. (2023). Performance analysis of a novel small-scale radial turbine with adjustable nozzle for ocean thermal energy conversion. AIP Advances.

3. Fu, X., & Sun, J. (2023). Three-dimensional color-gradient lattice Boltzmann model for simulating droplet ringlike migration under an omnidirectional thermal gradient. International Journal of Thermal Sciences.

4. Song, P., Sun, J., Wang, S., & Wang, X. (2022). Multipoint design optimization of a radial-outflow turbine for Kalina cycle system considering flexible operating conditions and variable ammonia-water mass fraction. Energies.

5. Song, P., Wang, S., & Sun, J. (2022). Numerical investigation and performance enhancement by means of geometric sensitivity analysis and parametric tuning of a radial-outflow high-pressure oil–gas turbine. Energies.

Assoc. Prof. Dr. Krishna Pada Das | Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Krishna Pada Das | Mathematics | Best Researcher Award

Associate Professor | Mahadevananda Mahavidyalaya | India

Assoc. Prof. Dr. Krishna Pada Das, a distinguished scholar in Mathematics, currently serves as an Associate Professor in the Department of Mathematics at Mahadevananda Mahavidyalaya, Barrackpore. His academic journey includes a Bachelor’s and Master’s degree in Mathematical Science from Calcutta University and a Doctorate in Applied Mathematics from Jadavpur University, where he conducted pioneering research under the supervision of Prof. Joydev Chattopadhyay at the Indian Statistical Institute. With extensive professional experience as a researcher and educator, he has contributed significantly to the field of Mathematics through his exploration of eco-epidemiological models, nonlinear dynamics, and bifurcation theory. His Mathematics research primarily focuses on the dynamics of predator-prey systems, infectious disease modeling, and population ecology using advanced mathematical tools such as fractional calculus, diffusion, stochastic processes, and delay differential equations. Over the course of his Mathematics career, Assoc. Prof. Dr. Krishna Pada Das has published more than ninety high-impact Mathematics research papers and guided multiple Ph.D. candidates in applied and computational Mathematics. His notable Mathematics achievements include the ISI Research Award and clearing the SLET examination, recognizing his exceptional academic and research proficiency in Mathematics. His Mathematics skills encompass mathematical modeling, numerical simulation using MATLAB, and analytical techniques for stability and chaos control in biological systems. In conclusion, his Mathematics contributions have strengthened interdisciplinary research connecting ecology, epidemiology, and applied mathematics, solidifying his position as a prominent researcher. Google Scholar profile of 1840 Citations, 23 h-index, 38 i10 index.

Profile: Google Scholar

Featured Publications

1. Das, K., & Mukherjee, A. K. (2007). Differential utilization of pyrene as the sole source of carbon by Bacillus subtilis and Pseudomonas aeruginosa strains: Role of biosurfactants in enhancing. Journal of Applied Microbiology, 102(1), 195–203.

2. Dutta, S. K., Das, K., Ghosh, B., & Blackman, C. F. (1992). Dose dependence of acetylcholinesterase activity in neuroblastoma cells exposed to modulated radio‐frequency electromagnetic radiation. Bioelectromagnetics, 13(4), 317–322.

3. Soni, B. K., Das, K., & Ghose, T. K. (1982). Bioconversion of agro-wastes into acetone butanol. Biotechnology Letters, 4(1), 19–22.

4. Kooi, B. W., van Voorn, G. A. K., & Das, K. P. (2011). Stabilization and complex dynamics in a predator–prey model with predator suffering from an infectious disease. Ecological Complexity, 8(1), 113–122.

5. Das, C. R., Mondal, N. K., Aditya, P., Datta, J. K., Banerjee, A., & Das, K. (2012). Allelopathic potentialities of leachates of leaf litter of some selected tree species on gram seeds under laboratory conditions. Asian Journal of Experimental Biological Sciences, 3(1), 59–65.*

Sathya Arumugam Thirumalai | Computational Methods | Young Scientist Award

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Mr. Sathya Arumugam Thirumalai | Computational Methods | Young Scientist Award

Mr. Sathya Arumugam Thirumalai | Indian Institute of Technology Roorkee | India

Mr. Sathya Arumugam Thirumalai is a highly motivated researcher whose work integrates Computational Methods with experimental nanomaterial science, emphasizing sustainability, environmental protection, and advanced detection technologies. His academic journey, from IIT Roorkee to TU Dresden, reflects an enduring commitment to merging experimental nanotechnology with Computational Methods for the synthesis and characterization of perovskite, MXene, and 2D materials. Mr. Sathya’s professional experience spans renowned institutions like IISc Bengaluru, BARC Mumbai, and IIT Roorkee, where he utilized Computational Methods in density functional theory (DFT) simulations, material modeling, and radiation detector design. His research, grounded in Computational Methods, has contributed to multiple journal publications addressing gas sensing, field emission, and radiation detection. He applies Computational Methods to optimize nanomaterial performance, enhance photonic properties, and improve the efficiency of radiation detectors. Recognized with several awards and fellowships, including the National Talent Search Fellowship and the Saxon Student Mobility Grant, he has demonstrated excellence in both theoretical and practical domains. His technical mastery extends to Python, MATLAB, COMSOL, and VASP, emphasizing his strength in applying Computational Methods across interdisciplinary fields. Mr. Sathya’s skill in Computational Methods enables him to bridge theoretical simulations with experimental validation, ensuring scientific precision and innovation. His collaborative engagements with global research groups highlight his leadership and cross-disciplinary adaptability. In conclusion, Mr. Sathya exemplifies how Computational Methods can revolutionize material science, fostering technological advancements that align with sustainability and human welfare.

Profiles: Google Scholar | ORCID

Featured Publications

1. Sathya, A. T., Jethawa, U., Sarkar, S. G., & Chakraborty, B. (2025). Pd-decorated MoSi₂N₄ monolayer: Enhanced nitrobenzene sensing through DFT perspective. Journal of Molecular Liquids, 427, 127310.

2. Sathya, A. T., Kandasamy, M., & Chakraborty, B. (2024). Strain induced nitrobenzene sensing performance of MoSi₂N₄ monolayer: Investigation from density functional theory. Surfaces and Interfaces, 55, 105386.

3. Sanyal, G., Vaidyanathan, A., Sathya, A. T., & Chakraborty, B. (2025). Efficient catechol sensing in newly synthesized 2D material Ti₂B MBene: Insights from density functional theory simulations. Langmuir, 41(33), 22525–22534.

4. Sathya, A. T., Sarkar, S. G., Bakhtsingh, R. I., & Mondal, J. (2024). Suppression of shielding effect of large area field emitter cathode in radio frequency gun environment. Physica Scripta, 99(12), 125301.

Prof. Viktor Mykhas’kiv | Computational Methods | Best Researcher Award

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Prof. Viktor Mykhas’kiv | Computational Methods | Best Researcher Award

Leading Scientific Researcher | Institute for Applied Problemss of Mechanics and Mathematics | Ukraine

Prof. Viktor Mykhas’kiv is a distinguished researcher at the Pidstryhach Institute for Applied Problems of Mechanics and Mathematics, National Academy of Sciences of Ukraine. His academic achievements include a Doctor of Science in Physics and Mathematics and a professorship in Mechanics of Deformable Solids. His extensive expertise in Computational Methods spans across Computational Mechanics, Materials Science, Structural Mechanics, and Multiscale Mathematical Modeling. Through his pioneering work, he has applied Computational Methods to study wave propagation, metamaterials, and nanomechanics, advancing knowledge in multiple scattering theory. His research leadership in international collaborations under INTAS, STCU, DAAD, DFG, and Fulbright programs highlights his ability to integrate Computational Methods within global scientific frameworks. As a team leader and project manager, he has promoted innovative Computational Methods in the investigation of elastic metamaterials and complex lattice structures. He has published widely, authoring over seventy-six Scopus-indexed papers, two books, and contributing to editorial boards of international journals like Mathematical Methods and Physicomechanical Fields. His commitment to excellence in Computational Methods is reflected in his role as a member of the European Structural Integrity Society. He has also served as a visiting researcher in the USA and Germany, applying Computational Methods to solve advanced mechanical and physical problems. His awards and honors recognize his groundbreaking use of Computational Methods in applied mechanics and theoretical modeling. With remarkable research skills and professional integrity, Prof. Viktor Mykhas’kiv continues to contribute significantly to global scientific progress. Scopus profile of 474 Citations, 76 Documents, 14 h-index.

Profiles: Scopus | ORCID

Featured Publications

1. Stankevych, V. Z., & Mykhas’kiv, V. V. (2023). Intensity of dynamic stresses of longitudinal shear in a periodically layered composite with penny-shaped cracks. Journal of Mathematical Sciences, 269(2), 268–280.

2. Mykhas’kiv, V. V., & Stasyuk, B. M. (2021). Effective elastic moduli of short-fiber composite with sliding contact conditions at interfaces. Mechanics of Composite Materials, 57(6), 845–854.

3. Mykhas’kiv, V., & Stankevych, V. (2019). Elastodynamic problem for a layered composite with penny-shaped crack under harmonic torsion. ZAMM – Zeitschrift für Angewandte Mathematik und Mechanik, 99(8), e201800193.

4. Mykhas’kiv, V. V., Zhbadynskyi, I. Y., & Zhang, C. (2019). On propagation of time-harmonic elastic waves through a double-periodic array of penny-shaped cracks. European Journal of Mechanics - A/Solids, 74, 68–77.

5. Zhbadynskyi, I. Y., & Mykhas’kiv, V. V. (2018). Acoustic filtering properties of 3D elastic metamaterials structured by crack-like inclusions. Proceedings of the International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED), 54–59.

Assist. Prof. Dr. Reem Abdullah Sadan Aljethi | Differentiation equation | Best Researcher Award

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Assist. Prof. Dr. Reem Abdullah Sadan Aljethi | Differentiation equation | Best Researcher Award

Associate Professor | Imam Mohammad Ibn Saud Islamic University | Saudi Arabia

Assist. Prof. Dr. Reem Abdullah Sadan Aljethi is an accomplished scholar in Applied Mathematics whose expertise lies prominently in the study and advancement of Differentiation Equation systems. Her academic journey, including a Doctor of Philosophy from Universiti Putra Malaysia and earlier degrees from King Saud University, shaped her deep engagement with Differentiation Equation models and fractional calculus. With professional experience as a Lecturer, Vice Dean, and currently an Associate Professor at Imam Mohammad Ibn Saud Islamic University, she has significantly contributed to teaching, research, and academic administration. Her research explores fractional Differentiation Equation formulations, Lévy stochastic processes, and applications in financial and physical systems. Her Q1-ranked publications in journals like Mathematics and Chaos, Solitons & Fractals highlight her command of complex Differentiation Equation frameworks. Recognized through her participation in international conferences and leadership programs, she exhibits strong analytical and computational skills, particularly in MATLAB and mathematical modeling. Her dedication to the Differentiation Equation field continues to influence emerging studies in nonlinear systems, fractional models, and applied mathematics. Overall, Assist. Prof. Dr. Reem Abdullah Sadan Aljethi’s scholarly path exemplifies excellence, innovation, and leadership in the global study of Differentiation Equation research and its expanding interdisciplinary applications.

Profiles: Google Scholar | ORCID

Featured Publications

1. Aljethi, R. A., & Kılıçman, A. (2022). Financial applications on fractional Lévy stochastic processes. Fractal and Fractional, 6(5), 278.

2. Aljethi, R. A., & Kılıçman, A. (2023). Analysis of fractional differential equation and its application to realistic data. Chaos, Solitons & Fractals, 171, 113446.

3. Aljethi, R. A., & Kılıçman, A. (2023). Derivation of the fractional Fokker–Planck equation for stable Lévy with financial applications. Mathematics, 11(5), 1102.

4. Aljedhi, R. A., & Kılıçman, A. (2020). Fractional partial differential equations associated with Lévy stable process. Mathematics, 8(4), 508.

5. Ejaz Hussain, U. Y., Aljethi, R. A., & Farooq, K. (2025). Optical multi-peakon dynamics in the fractional cubic–quintic nonlinear pulse propagation model using a novel integral approach. Fractal and Fractional, 9(10), 631.

Dr. Bahadir Kopcasiz | Computational Methods | Best Researcher Award

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Dr. Bahadir Kopcasiz | Computational Methods | Best Researcher Award

Assistant Professor | Istanbul Gelisim University | Turkey

Dr. Bahadir Kopcasiz is an accomplished academic whose expertise centers on Computational Methods, with strong emphasis on nonlinear partial differential equations, soliton theory, symbolic and semi-analytical analysis, and advanced mathematical modeling. He earned his Ph.D. in Mathematics from Bursa Uludag University, preceded by a Master’s in Mathematics from Yeditepe University and a Bachelor’s from Karadeniz Technical University, building a solid foundation for his contributions in Computational Methods. Currently serving as an Assistant Professor at Istanbul Gelisim University, he actively teaches courses such as Differential Equations, Statistics, Probability, and Numerical Analysis, integrating Computational Methods into both undergraduate and graduate programs. His research primarily focuses on soliton solutions in nonlinear Schrödinger-type systems, dynamical structures in quantum physics, and the development of innovative Computational Methods to study complex dynamical systems, with numerous publications in high-impact journals including Archives of Computational Methods in Engineering, Nonlinear Dynamics, and Symmetry. He has also presented extensively at international conferences, showcasing advancements in Computational Methods for applied physics and engineering. Among his recognitions, he received the Best Researcher Award at the International Research Awards on Composite Materials and academic incentive awards from Istanbul Gelisim University, which highlight his outstanding scholarly contributions in Computational Methods. His research skills are distinguished by mastery of symbolic computation, semi-analytical modeling, and integration of Computational Methods with machine learning for dynamic system optimization, as evidenced by his involvement in national projects. In conclusion, Dr. Bahadir Kopcasiz exemplifies excellence in academia through his dedication to advancing Computational Methods, innovative problem-solving, impactful publications, and mentorship, establishing himself as a valuable contributor to mathematics, physics, and engineering research. His Google Scholar citations 337, h-index 12, i10-index 14, showcasing measurable research impact.

Profiles: Google Scholar | ORCID

Featured Publications

1. Kopçasız, B., & Yaşar, E. (2022). The investigation of unique optical soliton solutions for dual-mode nonlinear Schrödinger’s equation with new mechanisms. Journal of Optics, 1–15.

2. Kopçasız, B., & Yaşar, E. (2022). Novel exact solutions and bifurcation analysis to dual-mode nonlinear Schrödinger equation. Journal of Ocean Engineering and Science.

3. Kopçasız, B., & Yaşar, E. (2024). Dual-mode nonlinear Schrödinger equation (DMNLSE): Lie group analysis, group invariant solutions, and conservation laws. International Journal of Modern Physics B, 38(02), 2450020.

4. Kopçasız, B. (2024). Qualitative analysis and optical soliton solutions galore: Scrutinizing the (2+1)-dimensional complex modified Korteweg–de Vries system. Nonlinear Dynamics, 112(23), 21321–21341.

5. Kopçasız, B., Seadawy, A. R., & Yaşar, E. (2022). Highly dispersive optical soliton molecules to dual-mode nonlinear Schrödinger wave equation in cubic law media. Optical and Quantum Electronics, 54(3), 194.

Dr. Prity Kumari | Mathematics | Women Researcher Award

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Dr. Prity Kumari | Mathematics | Women Researcher Award

PhD scholar | National Institute of Technology | India

Dr. Prity Kumari is an accomplished researcher in Mathematics with expertise in graph theory, combinatorics, cryptography, wireless sensor networks, and machine learning, demonstrating a strong academic and professional foundation through advanced studies and significant teaching experience in engineering mathematics, numerical methods, and discrete mathematics. Her doctoral work focused on the application of combinatorial design in wireless sensor networks, reflecting her depth in both theoretical and applied Mathematics. She has published impactful research in reputed SCIE and Q1/Q2 journals, contributing to key areas like group key management, cryptographic security, and re-keying prediction models using Mathematics-driven combinatorial and machine learning approaches. With fellowships, merit-based scholarships, and active participation in national-level workshops on post-quantum cryptography, cyber security, and Mathematics for machine learning, she has broadened her expertise and collaborative exposure. Dr. Prity Kumari has also enriched her professional skills through roles as a Mathematics faculty and teaching assistant, guiding learners in foundational and advanced topics of Mathematics. Her research skills highlight proficiency in combinatorial design, cryptographic applications, algorithmic development, and predictive modeling, aligning with cutting-edge directions in Mathematics and computer science. Awards, honors, and fellowships further strengthen her academic profile, demonstrating excellence and commitment. Beyond research, she engaged in leadership roles like hostel representative, reflecting organizational and interpersonal abilities. In conclusion, Dr. Prity Kumari embodies a Mathematics scholar whose contributions interconnect combinatorial structures, cryptographic security, and applied computational methods, making her a valuable academic and researcher with strong potential for further advancing the field of Mathematics.

Profiles: Google Scholar | ORCID

Featured Publications

1. Kumari, P., & Singh, K. R. (2024). Re-keying analysis in group key management of wireless sensor networks. Cryptography and Communications, 16(3), 665–677.

2. Mandal, R. K. P. K. N. R. D. S. S. K. (2024). Experimental comparison of pool boiling characteristics between CNT, GO, and CNT + GO-coated copper substrate. Heat Transfer. Advance online publication.

3. Kumar, P. K. K. R. S. R. (2025). Stacking ensemble algorithm to predict re-keying in group key management. Arabian Journal for Science and Engineering, 1–15.

4. Pegu, J., Singh, K. R., Kumari, P., & Mishra, V. N. (2025). Decomposition of corona graph. Filomat, 39(10), 3321–3328.

5. Kumari, P., & Singh, K. R. (2025). Re-keying in group key management for wireless sensor network using nested balanced incomplete block designs. IETE Journal of Research, 1–13.

Dr. Akinbo Bayo Johnson | Mathematics | Best Researcher Award

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Dr. Akinbo Bayo Johnson | Mathematics | Best Researcher Award

Senior Lecturer | Federal College of Education, Abeokuta, Nigeria and Postdoctoral researcher at Universidade Federal De Itajuba | Brazil 

Dr. Akinbo Bayo Johnson is a distinguished scholar in applied mathematics whose expertise spans fluid dynamics, entropy generation, nano and non-Newtonian fluids, thermodynamic models, and computational mathematics. With a Ph.D. in applied mathematics and solid foundations from advanced studies in mathematics, his academic journey has been dedicated to advancing theoretical and applied aspects of mathematics. He has served as a lecturer, senior researcher, and currently contributes as a postdoctoral researcher in Brazil, showcasing professional experience across teaching, supervision, and international research collaborations. His research interests are deeply rooted in mathematics, where he explores bioconvectional fluids, heat and mass transfer, and mathematical modeling, all of which have resulted in impactful publications in high-ranking journals. Dr. Akinbo has been honored with awards such as the Best Paper Award, Tetfund Postdoctoral Award, and multiple recognitions from scientific associations, reflecting his excellence in mathematics-driven research. His professional memberships in the Mathematical Association of Nigeria and related bodies further highlight his integration within the mathematics community. Skilled in MATHEMATICA programming and computational approaches, he has applied mathematics extensively in solving differential equations, thermodynamic systems, and fluid mechanics problems. His career demonstrates consistent contributions as a reviewer for international journals, strengthening the dissemination of mathematical knowledge. Overall, Dr. Akinbo Bayo Johnson embodies a commitment to mathematics through education, research, and professional service, and his dedication ensures that mathematics remains a vital tool in addressing complex scientific challenges while inspiring the next generation of mathematics researchers.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

1. Akinbo, B. J., & Olajuwon, B. I. (2023). Impact of radiation and heat generation/absorption in a Walters’ B fluid through a porous medium with thermal and thermo diffusion in the presence of chemical reaction. International Journal of Modelling and Simulation, 43(2), 87–100.

2. Akinbo, B. J., & Olajuwon, B. I. (2021). Impact of radiation and chemical reaction on stagnation-point flow of hydromagnetic Walters' B fluid with Newtonian heating. International Communications in Heat and Mass Transfer, 121, 105115.

3. Akinbo, B. J., & Olajuwon, B. I. (2019). Homotopy analysis investigation of heat and mass transfer flow past a vertical porous medium in the presence of heat source. International Journal of Heat & Technology, 37(3).

4. Akinbo, B. J., & Olajuwon, B. I. (2021). Radiation and thermal-diffusion interaction on stagnation-point flow of Walters' B fluid toward a vertical stretching sheet. International Communications in Heat and Mass Transfer, 126, 105471.

5. Akinbo, B. J., & Olajuwon, B. I. (2021). Heat transfer analysis in a hydromagnetic Walters' B fluid with elastic deformation and Newtonian heating. Heat Transfer, 50(3), 2033–2048.

6. Akinbo, B. J., Faniran, T., & Ayoola, E. O. (2015). Numerical solution of stochastic differential equations. International Journal of Advanced Research in Science, Engineering and Technology.

7. Akinbo, B. J., & Olajuwon, B. I. (2019). Heat and mass transfer in magnetohydrodynamics (MHD) flow over a moving vertical plate with convective boundary condition in the presence of thermal radiation. Sigma Journal of Engineering and Natural Sciences, 37(3), 1031–1053.

8. Akinbo, B. (2021). Influence of convective boundary condition on heat and mass transfer in a Walters’ B fluid over a vertical stretching surface with thermal-diffusion effect. Journal of Thermal Engineering, 7(7), 1784–1796.

9. Akinbo, B. J., & Olajuwon, B. I. (2019). Convective heat and mass transfer in electrically conducting flow past a vertical plate embedded in a porous medium in the presence of thermal radiation and thermo diffusion. Computational Thermal Sciences: An International Journal, 11(4).

10. Akinbo, B. J., & Olajuwon, B. I. (2025). Significance of Cattaneo-Christov heat flux model and heat generation/absorption with chemical reaction in Walters’ B fluid via a porous medium in the presence of Newtonian heating. International Journal of Modelling and Simulation, 45(1), 137–146.

Dr. Suliman Khan | Numerical Analysis | Best Researcher Award

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Dr. Suliman Khan | Numerical Analysis | Best Researcher Award

Postdoctoral Fellow at Nanjing University of Aeronautics and Astronautics | China

Numerical Analysis defines the foundation of Dr. Suliman Khan’s academic journey. His summary reflects a deep commitment to exploring the complexities of Numerical Analysis in both theoretical and applied domains. With a focus on highly oscillatory problems and physics-informed models, he uses Numerical Analysis as a tool to solve challenging equations. He integrates Numerical Analysis with machine learning, structural mechanics, and PDEs modeling, creating innovative solutions to real-world problems. His vision aligns Numerical Analysis research with education, fostering critical thinking and inspiring future mathematicians. This summary illustrates how Numerical Analysis serves as the bridge between computational advancements and practical applications, enabling continuous growth in modern scientific computing, engineering collaborations, and advanced mathematical problem-solving.

Professional Profiles 

Google Scholar Profile | ORCID Profile

Education 

Dr. Suliman Khan’s education centers around mastering the field of Numerical Analysis through rigorous training and research. His academic progression reflects a sustained focus on Numerical Analysis in applied mathematics, computational mathematics, and scientific computing. He pursued advanced degrees emphasizing Numerical Analysis and integral equations with oscillatory kernels, deepening his expertise in solving complex integrals. His thesis projects and research topics demonstrate advanced Numerical Analysis techniques, bridging oscillatory integral computation with practical boundary element methods. This education path builds the analytical foundation necessary for solving PDEs, developing innovative algorithms, and contributing to global Numerical Analysis research communities. By integrating theoretical understanding with computational practice, his academic training stands as a model for excellence in Numerical Analysis education.

Experience 

Dr. Suliman Khan’s professional experience reflects an application-driven approach to Numerical Analysis across international academic and research environments. Through postdoctoral fellowships, he enhanced Numerical Analysis techniques for aerospace structures and advanced computational modeling. He engaged in teaching roles, conveying Numerical Analysis principles to undergraduate and postgraduate students, guiding them in applying Numerical Analysis methods to solve mathematical and engineering problems. His responsibilities included supervising projects, delivering specialized lectures, and contributing to research teams developing Numerical Analysis-based simulations. This combination of teaching, research, and collaboration allowed him to evolve Numerical Analysis applications in boundary integral equations, structural mechanics, and scientific computing. His professional journey continues to strengthen global connections while advancing Numerical Analysis research and its innovative applications.

Research Interest 

Dr. Suliman Khan’s research interest revolves around extending the frontiers of Numerical Analysis to address modern mathematical and engineering challenges. His primary focus includes highly oscillatory problems, integral equations, and PDE modeling through Numerical Analysis techniques. He investigates physics-informed neural networks (PINNs), using Numerical Analysis to integrate computational intelligence with differential equations. His interests span radial basis functions, structural mechanics modeling, and Euler-Bernoulli and Timoshenko beam simulations, all rooted in Numerical Analysis frameworks. He explores computational strategies that combine theoretical precision with practical scalability, ensuring Numerical Analysis remains a driving force in scientific discovery. These research directions ensure Numerical Analysis serves not only academic curiosity but also industry-relevant innovation, bridging mathematical rigor with real-world applications.

Award and Honor

Recognition of Dr. Suliman Khan’s contributions to Numerical Analysis is reflected in various awards and honors. He received prestigious scholarships and appreciation certificates acknowledging his dedication to Numerical Analysis research and teaching. His leadership roles in academic networks highlight his commitment to promoting Numerical Analysis as an essential discipline within mathematics and engineering. His efforts to integrate Numerical Analysis into computational science have earned respect among peers globally. Through continuous involvement in high-impact projects, he represents a model of professional integrity and scholarly excellence. These honors validate his vision of advancing Numerical Analysis beyond theoretical studies, contributing significantly to applied mathematics, computational modeling, and collaborative problem-solving in multidisciplinary scientific environments.

Research Skill

Dr. Suliman Khan demonstrates advanced research skills in Numerical Analysis, combining theoretical insights with computational innovation. He develops efficient algorithms for highly oscillatory integrals, applying Numerical Analysis methods to solve integral equations and boundary element problems. His skills extend to machine learning integration, where Numerical Analysis underpins physics-informed neural networks for solving PDEs. He is proficient in mathematical programming languages, simulation environments, and model validation frameworks that rely on Numerical Analysis accuracy. He applies rigorous error analysis, stability checks, and convergence testing, ensuring Numerical Analysis results meet scientific standards. These skills collectively enable groundbreaking contributions to both mathematics and engineering, proving how Numerical Analysis serves as a foundation for modern computational problem-solving.

Publication Top Notes 

Title: Comparative study on heat transfer and friction drag in the flow of various hybrid nanofluids effected by aligned magnetic field and nonlinear radiation
Year: 2021
Citation: 82

Title: Entropy generation approach with heat and mass transfer in magnetohydrodynamic stagnation point flow of a tangent hyperbolic nanofluid
Year: 2021
Citation: 69

Title: Identifying the potentials for charge transport layers free np homojunction-based perovskite solar cells
Year: 2022
Citation: 24

Title: Antisolvent-fumigated grain growth of active layer for efficient perovskite solar cells
Year: 2021
Citation: 22

Title: A well-conditioned and efficient Levin method for highly oscillatory integrals with compactly supported radial basis functions
Year: 2021
Citation: 20

Title: Approximation of Cauchy-type singular integrals with high frequency Fourier kernel
Year: 2021
Citation: 19

Title: On the evaluation of highly oscillatory integrals with high frequency
Year: 2020
Citation: 15

Title: A dual interpolation boundary face method with Hermite-type approximation for elasticity problems
Year: 2020
Citation: 13

Title: An Accurate Computation of Highly Oscillatory Integrals with Critical Points
Year: 2018
Citation: 11

Title: A well-conditioned and efficient implementation of dual reciprocity method for Poisson equation
Year: 2021
Citation: 10

Title: Approximation of oscillatory Bessel integral transforms
Year: 2023
Citation: 9

Title: Numerical Investigation of the Fredholm Integral Equations with Oscillatory Kernels Based on Compactly Supported Radial Basis Functions
Year: 2022
Citation: 6

Title: Numerical approximation of Volterra integral equations with highly oscillatory kernels
Year: 2024
Citation: 5

Title: On the evaluation of Poisson equation with dual interpolation boundary face method
Year: 2021
Citation: 5

Title: A new implementation of DRM with dual interpolation boundary face method for Poisson equation
Year: 2020
Citation: 5

Title: Interpolation based formulation of the oscillatory finite Hilbert transforms
Year: 2022
Citation: 4

Title: On the Convergence Rate of Clenshaw–Curtis Quadrature for Jacobi Weight Applied to Functions with Algebraic Endpoint Singularities
Year: 2020
Citation: 4

Title: On Numerical Computation of Oscillatory Integrals and Integral Equations with Oscillatory Kernels
Year: 2021
Citation: 3

Title: A multiscale domain decomposition approach for parabolic equations using expanded mixed method
Year: 2022
Citation: 2

Title: On Computation of Bessel and Airy Oscillatory Integral Transforms
Year: 2025
Citation: 1

Conclusion

The academic and professional path of Dr. Suliman Khan underscores the transformative power of Numerical Analysis in modern science. His contributions demonstrate how Numerical Analysis enables theoretical breakthroughs and practical engineering solutions. Through teaching, research, and collaboration, he advances Numerical Analysis from abstract computation to actionable methodologies. His dedication ensures Numerical Analysis remains at the heart of applied mathematics, computational modeling, and machine learning integration. The conclusion of this narrative reflects his commitment to leveraging Numerical Analysis for global scientific progress. His vision inspires future mathematicians to embrace Numerical Analysis not just as a field of study but as a dynamic, problem-solving tool for advancing human knowledge.