Dr. Bahadir Kopcasiz | Computational Methods | Best Researcher Award

Published on 17/09/202517/09/2025 by Physicist Particle

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. Suliman Khan | Numerical Analysis | Best Researcher Award

Published on 10/09/202510/09/2025 by Physicist Particle

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.

Prof. Ahmed Ouadha | Computational Methods | Best Researcher Award

Published on 03/09/202503/09/2025 by Physicist Particle

Prof. Ahmed Ouadha | Computational Methods | Best Researcher Award

Prof at USTO-MB | Algeria

Prof. Ahmed Ouadha is a distinguished academic specializing in energy systems and marine engineering. His expertise covers thermodynamics, refrigeration, marine diesel engines, and exergy analysis with a strong integration of Computational Methods. His career reflects a commitment to advancing innovative Computational Methods for analyzing complex thermal and fluid systems. Through Computational Methods, he has contributed extensively to the optimization of marine propulsion and refrigeration cycles. Prof. Ouadha’s leadership in academic and industrial collaborations strengthens the practical application of Computational Methods in engineering research. He continues to explore new Computational Methods to address emerging challenges in sustainable energy systems, positioning himself at the forefront of technological advancement in marine and mechanical engineering fields globally.

Professional Profiles

Google Scholar Profile | ORCID Profile | Scopus Profile

Education

Prof. Ahmed Ouadha obtained multiple degrees in energetic and marine engineering, providing a solid academic foundation for research and teaching. His educational journey focused on applying Computational Methods in thermodynamic systems, refrigeration cycles, and marine propulsion optimization. Advanced studies enabled him to integrate Computational Methods for exergy analysis, heat transfer modeling, and fluid mechanics simulations. The emphasis on Computational Methods throughout his education cultivated skills crucial for developing predictive models and enhancing system efficiency. His academic background demonstrates how Computational Methods can bridge theoretical analysis and industrial solutions. This comprehensive preparation established him as an expert capable of transforming Computational Methods into practical tools for innovative engineering applications.

Experience

Prof. Ahmed Ouadha has held academic positions advancing from lecturer to full professor in marine engineering, consistently applying Computational Methods to teaching, research, and industrial consultancy. His professional experience emphasizes the strategic use of Computational Methods in optimizing marine diesel engines, refrigeration systems, and energy recovery solutions. He has supervised numerous research projects where Computational Methods guided experimental designs, data analysis, and system modeling. Industrial training and consulting engagements benefited from Computational Methods to diagnose and improve ship performance. His professional path illustrates how Computational Methods drive innovation across education, research, and practical engineering domains, reinforcing his reputation as a leader in applying Computational Methods effectively.

Research Interest

Prof. Ahmed Ouadha’s research interests span thermodynamics, marine diesel engines, refrigeration, cryogenics, exergy analysis, and fluid dynamics, with Computational Methods serving as a core approach. He employs Computational Methods to simulate and optimize marine propulsion systems and heat transfer mechanisms, ensuring enhanced efficiency and sustainability. His focus includes applying Computational Methods to analyze alternative fuels, waste heat recovery cycles, and advanced refrigeration technologies. These Computational Methods support the development of predictive tools and environmentally responsible engineering solutions. By continuously integrating Computational Methods into evolving research areas, Prof. Ouadha advances the boundaries of knowledge while addressing pressing global energy and marine industry challenges.

Award and Honor

Prof. Ahmed Ouadha has been recognized for his exceptional academic and research contributions, often centered around the innovative application of Computational Methods. His work using Computational Methods in marine energy systems has earned distinctions in conferences and journals. These awards highlight the impact of Computational Methods in optimizing performance, reducing emissions, and improving sustainability in marine and thermal engineering. Honors received underscore his role as a pioneer integrating Computational Methods in multi-disciplinary projects. Through such achievements, he has elevated both academic standards and industrial practices, proving the transformative influence of Computational Methods in engineering advancements globally and inspiring future generations of researchers.

Research Skill

Prof. Ahmed Ouadha possesses a broad set of research skills rooted in Computational Methods. His expertise includes modeling thermodynamic cycles, simulating fluid dynamics, and conducting exergy and entropy analyses using Computational Methods. He demonstrates strong capabilities in designing and validating advanced engineering systems where Computational Methods enhance predictive accuracy. His skills extend to integrating Computational Methods with experimental approaches, yielding robust insights for marine propulsion and refrigeration systems. He effectively applies Computational Methods to develop innovative solutions addressing energy efficiency, emissions control, and sustainable operations. This mastery of Computational Methods positions him as an essential contributor to cutting-edge engineering research and practical technological progress.

Publication Top Notes

Title: Numerical study of energy separation in a vortex tube with different RANS models
Journal: International Journal of Thermal Sciences
Authors: M Baghdad, A Ouadha, O Imine, Y Addad
Citation: 108

Title: Integration of an ammonia-water absorption refrigeration system with a marine Diesel engine: A thermodynamic study
Journal: Procedia Computer Science
Authors: A Ouadha, Y El-Gotni
Citation: 94

Title: Effects of variable thermophysical properties on flow and energy separation in a vortex tube
Journal: International Journal of Refrigeration
Authors: A Ouadha, M Baghdad, Y Addad
Citation: 54

Title: Thermodynamic analysis of an HCCI engine based system running on natural gas
Journal: Energy Conversion and Management
Authors: M Djermouni, A Ouadha
Citation: 53

Title: Exergy analysis of a two-stage refrigeration cycle using two natural substitutes of HCFC22
Journal: International Journal of Exergy
Authors: A Ouadha, M En-Nacer, L Adjlout, O Imine
Citation: 51

Title: Combustion characteristics of hydrogen-rich alternative fuels in counter-flow diffusion flame configuration
Journal: Energy Conversion and Management
Authors: K Safer, F Tabet, A Ouadha, M Safer, I Gökalp
Citation: 34

Title: Thermodynamic analysis of methanol, ammonia, and hydrogen as alternative fuels in HCCI engines
Journal: International Journal of Thermofluids
Authors: M Djermouni, A Ouadha
Citation: 32

Title: Simulation of a syngas counter-flow diffusion flame structure and NO emissions in the pressure range 1–10 atm
Journal: Fuel Processing Technology
Authors: K Safer, F Tabet, A Ouadha, M Safer, I Gökalp
Citation: 32

Title: A numerical investigation of structure and emissions of oxygen-enriched syngas flame in counter-flow configuration
Journal: International Journal of Hydrogen Energy
Authors: M Safer, F Tabet, A Ouadha, K Safer
Citation: 28

Title: Comparative assessment of LNG and LPG in HCCI engines
Journal: Energy Procedia
Authors: M Djermouni, A Ouadha
Citation: 24

Title: An exergy analysis of various layouts of ORC-VCC systems for usage in waste heat recovery onboard ships
Journal: Marine Systems & Ocean Technology
Authors: O Bounefour, A Ouadha, Y Addad
Citation: 20

Title: Entropy generation in turbulent syngas counter-flow diffusion flames
Journal: International Journal of Hydrogen Energy
Authors: K Safer, A Ouadha, F Tabet
Citation: 18

Title: Performance comparison of cascade and two-stage refrigeration cycles using natural refrigerants
Journal: The 22nd International Congress of Refrigeration
Authors: A Ouadha, C Haddad, M En-Nacer, O Imine
Citation: 18

Title: Effects of kinetic energy and conductive solid walls on the flow and energy separation within a vortex tube
Journal: International Journal of Ambient Energy
Authors: M Baghdad, A Ouadha, Y Addad
Citation: 17

Title: Performance analysis of oxygen refrigerant in an LNG BOG re-liquefaction plant
Journal: Procedia Computer Science
Authors: BM Beladjine, A Ouadha, L Adjlout
Citation: 16

Title: Performance improvement of combined organic Rankine-vapor compression cycle using serial cascade evaporation in the organic cycle
Journal: Energy Procedia
Authors: O Bounefour, A Ouadha
Citation: 15

Title: Thermodynamic analysis and working fluid optimization of a combined ORC-VCC system using waste heat from a marine diesel engine
Journal: ASME International Mechanical Engineering Congress and Exposition
Authors: O Bounefour, A Ouadha
Citation: 13

Title: Flow and heat transfer features during propane (R290) and isobutane (R600a) boiling in a tube
Journal: International Journal of Thermofluids
Authors: R Fenouche, A Ouadha
Citation: 12

Title: Exergy analysis of an LNG BOG reliquefaction plant
Journal: Proceedings of the 23rd IIR International Congress of Refrigeration
Authors: BM Beladjine, A Ouadha, Y Benabdesslam, L Adjlout
Citation: 11

Title: CFD-based analysis of entropy generation in turbulent double diffusive natural convection flow in square cavity
Journal: MATEC Web of Conferences
Authors: K Said, A Ouadha, A Sabeur
Citation: 9

Conclusion

Prof. Ahmed Ouadha’s career exemplifies excellence in research, education, and innovation driven by Computational Methods. His contributions impact academic advancement, industrial efficiency, and environmental sustainability. By employing Computational Methods across multiple disciplines, he transforms theoretical concepts into practical solutions for marine propulsion, refrigeration, and energy systems. His leadership fosters collaborations where Computational Methods enable breakthroughs addressing contemporary engineering challenges. The consistency, depth, and vision in applying Computational Methods underline his status as a prominent figure in modern mechanical and marine engineering. Prof. Ouadha continues to shape the future of engineering education and technology, demonstrating how Computational Methods can inspire progress globally.

Assist. Prof. Dr. Kifle Adula Duguma | Computational Methods | Best Researcher Award

Published on 13/08/202513/08/2025 by Physicist Particle

Assist. Prof. Dr. Kifle Adula Duguma | Computational Methods | Best Researcher Award

Assistant Professor at Addis Ababa Science and Technology University, Ethiopia

Assist. Prof. Dr. Kifle Adula Duguma is a distinguished academic in the field of Computational Methods, dedicated to advancing knowledge in computational fluid dynamics, applied mathematics, and numerical analysis. His work on Computational Methods spans theoretical research, practical applications, and interdisciplinary collaboration. In his professional journey, Dr. Duguma has integrated Computational Methods into both undergraduate and postgraduate education, guiding students in research and project work. His publications in high-impact journals consistently emphasize Computational Methods for solving complex fluid flow, heat transfer, and porous media problems. By applying Computational Methods to nanofluid dynamics, magnetohydrodynamics, and hybrid modeling, he has contributed valuable insights to modern engineering problems. His academic leadership also promotes Computational Methods as a cornerstone of innovative problem-solving.

Professional Profile

ORCID Profile | Google Scholar Profile

Education

Assist. Prof. Dr. Kifle Adula Duguma has built his academic foundation through extensive studies in mathematics, numerical analysis, and computational fluid dynamics, always centered on Computational Methods. From undergraduate studies in mathematics to advanced doctoral research, Computational Methods formed the core of his learning. His doctoral thesis applied Computational Methods to complex flow and heat transfer problems, integrating theory with simulation. During his master’s degree, he refined his expertise in Computational Methods for solving nonlinear partial differential equations. Each academic stage strengthened his ability to innovate with Computational Methods, whether in finite element approaches, finite difference applications, or numerical modeling techniques. His training consistently reflects a deep engagement with Computational Methods, preparing him for impactful contributions in teaching and research.

Experience

Assist. Prof. Dr. Kifle Adula Duguma has extensive professional experience applying Computational Methods in both teaching and research. As an assistant professor, he has taught courses in applied mathematics, computational fluid dynamics, and numerical analysis, always embedding Computational Methods in lectures, laboratories, and projects. His leadership roles, including heading the mathematics division, emphasized curriculum design with strong Computational Methods components. His research applies Computational Methods to nanofluid flows, magnetohydrodynamics, hybrid models, and porous media. He supervises student projects that rely on Computational Methods for simulation and optimization. Across his career, Dr. Duguma has demonstrated that Computational Methods are essential in solving complex engineering problems, from industrial applications to academic challenges, ensuring students and peers value Computational Methods in their work.

Research Interest

Assist. Prof. Dr. Kifle Adula Duguma’s research interests revolve around the innovative application of Computational Methods in science and engineering. His primary focus areas include computational fluid dynamics, nanofluids, magnetohydrodynamics, electrohydrodynamics, and thermal transport phenomena, all driven by Computational Methods. He explores new algorithms, optimization techniques, and simulation strategies using Computational Methods for real-world problems. His studies in non-Newtonian fluids and hybrid nanofluids apply Computational Methods to enhance prediction accuracy and performance modeling. By integrating Computational Methods into multidisciplinary research, he addresses challenges in heat and mass transfer, stability analysis, and porous media flows. The consistent thread in his scholarly work is the advancement of Computational Methods as powerful tools for solving emerging engineering and scientific challenges worldwide.

Award and Honor

Assist. Prof. Dr. Kifle Adula Duguma’s academic achievements are closely linked to his pioneering contributions in Computational Methods. His recognition comes from publishing high-impact research where Computational Methods solve advanced engineering problems. Awards and honors highlight his leadership in integrating Computational Methods into both research and teaching. Serving as a journal reviewer, he evaluates work that applies Computational Methods across various domains. His leadership positions and contributions to academic communities are built upon advancing Computational Methods knowledge. These honors reflect not only technical expertise but also his ability to inspire others to apply Computational Methods in innovative ways. By consistently promoting Computational Methods, Dr. Duguma has earned respect as a leading figure in computational science and engineering.

Research Skill

Assist. Prof. Dr. Kifle Adula Duguma’s research skills are deeply rooted in Computational Methods, making him proficient in multiple numerical and analytical approaches. He expertly applies Computational Methods such as finite difference, finite element, finite volume, and Runge-Kutta techniques to model complex systems. His use of Computational Methods extends to software like MATLAB, Mathematica, Maple, and Python for simulation and analysis. He excels in data interpretation, algorithm development, and scientific computation, all grounded in Computational Methods. His capacity to integrate Computational Methods into experimental validation and theoretical frameworks strengthens his research output. Whether in teaching, mentoring, or publication, his skill set ensures Computational Methods remain central to his work and to the advancement of modern engineering practices globally.

Publication Top Notes

Title: Stability analysis of dual solutions of convective flow of casson nanofluid past a shrinking/stretching slippery sheet with thermophoresis and brownian motion in porous media

Authors: KA Duguma, OD Makinde, LG Enyadene

Journal: Journal of Mathematics

Title: Dual Solutions and Stability Analysis of Cu-H2O-Casson Nanofluid Convection past a Heated Stretching/Shrinking Slippery Sheet in a Porous Medium

Authors: KA Duguma, OD Makinde, LG Enyadene

Journal: Computational and Mathematical Methods

Title: Stagnation Point Flow of CoFe2O4/TiO2-H2O-Casson Nanofluid past a Slippery Stretching/Shrinking Cylindrical Surface in a Darcy–Forchheimer Porous Medium

Authors: KA Duguma, OD Makinde, LG Enyadene

Journal: Journal of Engineering

Title: Effects of buoyancy on radiative MHD mixed convective flow of casson nanofluid across a preamble slippery sheet in Darcy–Forchheimer porous medium: Shrinking/stretching surface …

Authors: KA Duguma

Journal: Numerical Heat Transfer, Part B: Fundamentals

Title: Stability Analysis of Dual Solutions of Convective Flow of Casson Nanofluid past a Shrinking/Stretching Slippery Sheet with Thermophoresis and Brownian Motion …

Authors: KA Duguma, OD Makinde, LG Enyadene

Journal: Journal of Mathematics

Conclusion

In conclusion, Assist. Prof. Dr. Kifle Adula Duguma’s career reflects unwavering dedication to Computational Methods in education, research, and professional service. His expertise ensures Computational Methods are applied rigorously across scientific domains, from computational fluid dynamics to nanotechnology. Through teaching, supervision, and publication, he promotes the strategic use of Computational Methods to solve critical engineering problems. His leadership in academic and research settings consistently elevates the role of Computational Methods as indispensable tools in modern science. By advancing Computational Methods methodologies, fostering innovation, and inspiring students, he has established a legacy that underscores the transformative power of Computational Methods in solving global scientific and technological challenges.

Dr. Seungpyo Lee | Computational Methods | Best Researcher Award

Published on 08/08/202508/08/2025 by Physicist Particle

Dr. Seungpyo Lee | Computational Methods | Best Researcher Award

Director at ILJIN Global, South Korea

Dr. Seungpyo Lee is an expert in computational methods with extensive research in computational methods for mechanical systems, especially in bearings. His focus lies in computational methods for finite element analysis, and he leads computational methods applications at ILJIN Global. Over the years, his work has demonstrated how computational methods enhance engineering outcomes. Dr. Seungpyo Lee utilizes computational methods in fatigue evaluation, stiffness prediction, and dynamic simulations. By implementing computational methods, he ensures accuracy, efficiency, and innovation. His leadership relies on computational methods to solve real-world mechanical challenges. Using computational methods, he fosters engineering advancements. Computational methods help define his professional profile. Through computational methods, Dr. Seungpyo Lee inspires others to pursue innovation via computational methods in research and development.

Professional Profile

Google Scholar

Education

Dr. Seungpyo Lee pursued all his degrees in mechanical engineering from Hanyang University, specializing in computational methods, particularly computational methods used in finite element analysis. Throughout his education, computational methods were central to his learning, research, and thesis. His academic foundation was enriched by computational methods in structural analysis and mechanics. He became proficient in computational methods while working on real-time simulation projects. Computational methods were crucial in solving engineering problems. His graduate studies included extensive work on computational methods in applied mechanics. Computational methods supported his skill development and critical thinking. Dr. Lee explored advanced topics in computational methods, integrating computational methods into core engineering applications. His commitment to computational methods began early and shaped his entire academic path.

Experience

Dr. Seungpyo Lee has applied computational methods throughout his career. At ILJIN Global, he leads the R&D Center's CAE team, where computational methods are a foundation of daily operations. His role includes integrating computational methods for mechanical simulations, design validation, and predictive maintenance. Dr. Lee manages teams that rely on computational methods to solve real-time problems. With computational methods, he evaluates bearing stiffness, friction, and fatigue. Computational methods allow his team to drive innovation and enhance product quality. His daily decisions are based on computational methods for simulation accuracy. Under his guidance, computational methods have transformed workflows. His experience reflects a deep understanding of computational methods. Dr. Lee continuously evolves professional practices using computational methods.

Research Interest

Dr. Seungpyo Lee’s research interests revolve around computational methods for CAE applications. He uses computational methods to study bearing performance, fatigue life, and structural behavior. His current research includes computational methods applied in AI-driven simulations. Dr. Lee combines computational methods with machine learning and deep learning. These advanced computational methods improve prediction accuracy. He investigates how computational methods optimize mechanical design. His research also evaluates computational methods in modeling torque and stiffness. Using computational methods, he addresses industry challenges. He frequently publishes studies exploring new computational methods. His research goal is to expand computational methods in automated analysis. Dr. Lee constantly explores frontiers of computational methods, enriching the engineering field with innovative computational methods-based solutions.

Award and Honor

Dr. Seungpyo Lee’s achievements are grounded in his expertise in computational methods. He has earned recognition for applying computational methods in mechanical simulations. His work with computational methods has received industry-wide acclaim. Dr. Lee’s use of computational methods in predictive modeling led to significant product innovation. Honors were awarded based on his contributions to computational methods in CAE analysis. He has led numerous projects where computational methods were essential. These projects highlight his mastery of computational methods in real-world scenarios. His honors celebrate dedication to advancing computational methods. Computational methods are central to every accolade he receives. His reputation as a leader in computational methods continues to grow. Dr. Lee’s accomplishments underscore the power of computational methods.

Research Skill

Dr. Seungpyo Lee’s research skills are rooted in computational methods, especially in finite element modeling. He excels in applying computational methods for stress analysis, fatigue simulation, and AI integration. His problem-solving approach uses computational methods extensively. With a strong command of simulation tools, he implements computational methods in various projects. His skill set includes writing algorithms and customizing tools based on computational methods. Dr. Lee can assess results through computational methods and improve accuracy. He adapts computational methods to new technologies. His ability to apply computational methods in different domains showcases versatility. Dr. Lee develops strategies using computational methods to solve complex problems. His proficiency ensures that computational methods remain central to research and development practices.

Publication Top Notes

Title: Probabilistic analysis for mechanical properties of glass/epoxy composites using homogenization method and Monte Carlo simulation
Authors: SP Lee, JW Jin, KW Kang
Journal: Renewable Energy

Title: Low and high cycle fatigue of automotive brake discs using coupled thermo-mechanical finite element analysis under thermal loading
Authors: MJ Han, CH Lee, TW Park, SP Lee
Journal: Journal of Mechanical Science and Technology

Title: Bearing life evaluation of automotive wheel bearing considering operation loading and rotation speed
Authors: SP Lee
Journal: Transactions of the Korean Society of Mechanical Engineers A

Title: Homogenization-based multiscale analysis for equivalent mechanical properties of nonwoven carbon-fiber fabric composites
Authors: H Lee, C Choi, J Jin, M Huh, S Lee, K Kang
Journal: Journal of Mechanical Science and Technology

Title: Distortion analysis for outer ring of automotive wheel bearing
Authors: SP Lee, BC Kim, IH Lee, YG Cho, YC Kim
Journal: Transactions of the Korean Society of Mechanical Engineers A

Title: Analysis for deformation behavior of multilayer ceramic capacitor based on multiscale homogenization approach
Authors: SP Lee, KW Kang
Journal: Journal of Mechanical Science and Technology

Title: The effect of outer ring flange concavity on automotive wheel bearings performance
Authors: S Lee, N Lee, J Lim, J Park
Journal: SAE International Journal of Passenger Cars - Mechanical Systems

Title: Structural design and analysis for small wind turbine blade
Authors: SP Lee, KW Kang, SM Chang, JH Lee
Journal: Journal of the Korean Society of Manufacturing Technology Engineers

Title: Deformation analysis of rubber seal assembly considering uncertainties in mechanical properties
Authors: SP Lee, KW Kang
Journal: Journal of Mechanical Science and Technology

Title: Fatigue analysis for automotive wheel bearing flanges
Authors: JW Jin, KW Kang, S Lee
Journal: International Journal of Precision Engineering and Manufacturing

Title: Life Evaluation of grease for ball bearings according to temperature, speed, and load changes
Authors: J Son, S Kim, BH Choi, S Lee
Journal: Tribology and Lubricants

Conclusion

Dr. Seungpyo Lee exemplifies leadership in computational methods across research, education, and industry. His consistent use of computational methods has advanced mechanical engineering practices. Whether in simulation, design, or research, computational methods are his core tool. Dr. Lee advocates for computational methods in problem-solving and innovation. Through team leadership and research, he advances computational methods. His knowledge of computational methods helps bridge academic theory and industrial practice. Dr. Lee’s influence ensures computational methods will remain integral to future developments. He continues to inspire others by promoting computational methods. His vision includes expanding computational methods to new frontiers. Dr. Lee's legacy will be closely tied to computational methods and their impact on engineering evolution.

Assist Prof Dr. Amirali Amirsoleimani | AI Hardware design | Best Scholar Award

Published on 09/08/202409/08/2024 by Physicist Particle

Assist Prof Dr. Amirali Amirsoleimani | AI Hardware design | Best Scholar Award

Assist Prof Dr. Amirali Amirsoleimani, York University, Canada

Dr. Amirali Amirsoleimani is an Assistant Professor at York University, Canada, with a strong background in Electrical and Computer Engineering. His research is dedicated to advancing AI and neuromorphic computing by integrating CMOS technology with emerging memory solutions and bio-inspired algorithms. He has received numerous accolades for his contributions, including the IEEE Larry K. Wilson Award and the Alumni Odyssey Award from the University of Windsor. Dr. Amirsoleimani’s work is focused on developing cutting-edge technologies for efficient, high-performance computing systems in smart environments.

PROFILE

Orcid

Education

Ph.D. in Electrical and Computer Engineering (Sep 2014 – Dec 2017)

University of Windsor, Windsor, ON, Canada

Dissertation: In-Memory Computing by Using Nano-ionic Memristive Devices

Advisor: Dr. Majid Ahmadi

External Examiner: Dr. Manoj Sachdev

M.Sc. in Electrical and Computer Engineering (Sep 2011 – Sep 2013)

Razi University, Kermanshah, Iran

Dissertation: Process Variation Analysis of CMOS and CMOS-Memristor Logic Gates

Advisor: Dr. Arash Ahmadi

B.Sc. in Electrical and Computer Engineering (Sep 2006 – Sep 2010)

Razi University, Kermanshah, Iran

Dissertation: Intelligent Digital Thermal Measurement with USB Data Transfer Protocol

Advisor: Dr. Reza Keyhani

Research Interest

Dr. Amirali Amirsoleimani’s research focuses on developing ultra-efficient artificial intelligence (AI) and neuromorphic computing solutions. His work involves the integration of CMOS circuits with emerging memory technologies such as RRAM and PCRAM, as well as bio-inspired spike-based computing algorithms. His goal is to design fully-integrated in-memory computing systems, employing a software-hardware co-design approach. Dr. Amirsoleimani leads an interdisciplinary team of experts to create innovative solutions at the device, circuit, and software levels, aimed at achieving low-power, high-performance AI for smart environments.

Professional Experience

Dr. Amirali Amirsoleimani is an Assistant Professor at York University, Canada. He has been recognized for his contributions to the field with the IEEE Larry K. Wilson Award in 2016, which is awarded to a single recipient annually in Canada. Dr. Amirsoleimani was also honored with a Best Poster Honorable Mention at the IEEE International Joint Conference on Neural Network in 2017. His involvement in IEEE has been notable, with various recognitions including Certificates of Recognition for his roles and contributions within the IEEE Windsor Section. Additionally, he received the Graduate Student Society (GSS) Scholarship in 2016, further highlighting his achievements in the academic and research communities.

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