Saif Ur Rehman | Applied Mathematics | Best Researcher Award

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Dr. Saif Ur Rehman | Applied Mathematics | Best Researcher Award

Research Assistant at Consiglio Nazionale delle Ricerche (CNR), Genoa, Italy, Pakistan.

Saif Ur Rehman is a dedicated researcher in Computational Fluid Dynamics (CFD), Numerical Analysis, and Partial Differential Equations, with a strong academic and research background. He has worked as a Research Assistant at the National Research Council, Italy, and previously at the University of Calabria, Italy, and the University of Management and Technology, Pakistan. His research focuses on nanofluid dynamics, MHD flows, bioconvection, and heat transfer, leading to multiple Q1 and Q2 publications in high-impact journals such as Nanomaterials, Mathematics, and Waves in Random and Complex Media. He has received merit-based scholarships and a Research Publication Award, demonstrating his academic excellence. Additionally, he possesses strong technical skills in Python, MATLAB, C++, and LaTeX, aiding in his numerical modeling research. With international research exposure and a growing publication record, Saif Ur Rehman is an emerging scholar in applied mathematics, aiming to expand his contributions to mathematical modeling and computational sciences.

Professional Profile 

Google Scholar

Education

Saif Ur Rehman holds a Master of Science in Mathematics from the University of Management and Technology, Lahore, Pakistan (2019–2021), where he specialized in Advanced Numerical Analysis, Fluid Dynamics, and Differential Equations. His master’s thesis focused on the MHD Williamson Nanofluid Flow over a Slender Elastic Sheet in the Presence of Bioconvection. Before this, he earned a Bachelor of Science in Mathematics from Government College University, Faisalabad (2015–2019), securing a 3.55/4.00 GPA. His undergraduate studies included Fluid Mechanics, Numerical Analysis, Real and Complex Analysis, and C++ Programming, laying a strong foundation for his research in computational mathematics. Throughout his academic journey, he received multiple merit-based scholarships, including the Punjab Education Endowment Fund Scholarship (PEEF) and a fully funded master’s scholarship, reflecting his dedication and academic excellence. His education has equipped him with expertise in mathematical modeling, numerical simulations, and applied mathematics, which he continues to explore in his research.

Professional Experience

Saif Ur Rehman has gained extensive research experience through multiple roles at renowned international institutions. He is currently a Research Assistant at the National Research Council, Genoa, Italy (2024–Present), working on Optimal Robust Shape Control for Distributed Parameter Systems. Previously, he was a University Research Assistant at the University of Calabria, Italy (2023–2024), focusing on applications of heat and mass transfer. His earlier role as a Research Assistant at the University of Management and Technology, Pakistan (2021–2023) involved a major research project on Numerical Methods for Partial Differential Equations, where he contributed to multiple high-impact publications. Alongside research, he worked as a Visiting Lecturer in Mathematics (2021–2022), teaching Calculus, Linear Algebra, Fluid Dynamics, and Numerical Analysis at the undergraduate level. His professional experience demonstrates his ability to conduct applied mathematics research, develop numerical solutions, and contribute to theoretical and computational fluid dynamics.

Research Interest

Saif Ur Rehman’s research is deeply rooted in Computational Fluid Dynamics (CFD), Numerical Analysis, and Partial Differential Equations (PDEs), with a strong focus on heat and mass transfer, MHD flows, and bioconvection. He has extensively studied the dynamics of nanofluids, micropolar fluids, and dusty fluids under various physical constraints, contributing significantly to theoretical and computational modeling in applied mathematics. His work integrates Artificial Neural Networks (ANNs) and Machine Learning techniques to enhance numerical simulations and solve complex mathematical physics problems. His research contributions, published in Q1 and Q2 impact factor journals, cover topics such as the effects of Lorentz and Coriolis forces, Darcy–Forchheimer flow models, and stability analysis of fluid flows. With expertise in Python, MATLAB, C++, and LaTeX, he continues to explore innovative numerical methods for solving real-world mathematical problems, aiming to bridge the gap between theory and industrial applications.

Awards and Honors

Saif Ur Rehman has received multiple scholarships and research excellence awards in recognition of his academic achievements. He was honored with the Research Publication Award (2022) at the University of Management and Technology, Pakistan, for his outstanding contributions to applied mathematics research. His academic journey has been supported by fully funded merit-based scholarships, including the Punjab Education Endowment Fund Scholarship (PEEF) during his bachelor’s studies and a fully funded master’s scholarship for his postgraduate studies. Additionally, he was awarded a Prime Minister’s Laptop under the Government of Pakistan’s Higher Education Initiative, recognizing his academic excellence. Beyond research, he has demonstrated leadership and management skills, serving as a class representative throughout his bachelor’s studies and actively participating in academic societies and awards. His awards reflect his dedication to mathematical research, academic excellence, and contributions to the global scientific community.

Conclusion

Saif Ur Rehman is an emerging researcher in Computational Fluid Dynamics, Numerical Analysis, and Partial Differential Equations, with a strong academic background and international research exposure. His work in nanofluid dynamics, MHD flows, and heat transfer has resulted in high-impact publications and significant contributions to applied mathematics. His expertise in Python, MATLAB, and numerical modeling techniques has strengthened his research capabilities. Having worked at renowned institutions in Italy and Pakistan, he has gained experience in both theoretical and applied research, positioning himself as a promising scholar in mathematical modeling and computational sciences. His awards, scholarships, and research achievements demonstrate his dedication to scientific innovation. Moving forward, he aims to further his research in numerical simulations, machine learning applications in CFD, and advanced mathematical modeling, contributing to both academic advancements and real-world engineering applications.

Publications Top Noted

  • Title: Insight into significance of bioconvection on MHD tangent hyperbolic nanofluid flow of irregular thickness across a slender elastic surface

    • Authors: MZ Ashraf, SU Rehman, S Farid, AK Hussein, B Ali, NA Shah, W Weera
    • Year: 2022
    • Citations: 92
    • Source: Mathematics, 10(15), 2592

  • Title: Numerical computation of buoyancy and radiation effects on MHD micropolar nanofluid flow over a stretching/shrinking sheet with heat source

    • Authors: SU Rehman, A Mariam, A Ullah, MI Asjad, MY Bajuri, BA Pansera, et al.
    • Year: 2021
    • Citations: 86
    • Source: Case Studies in Thermal Engineering, 25, 100867

  • Title: Micropolar dusty fluid: Coriolis force effects on dynamics of MHD rotating fluid when Lorentz force is significant

    • Authors: Q Lou, B Ali, SU Rehman, D Habib, S Abdal, NA Shah, JD Chung
    • Year: 2022
    • Citations: 84
    • Source: Mathematics, 10(15), 2630

  • Title: The Casson dusty nanofluid: Significance of Darcy–Forchheimer law, magnetic field, and non-Fourier heat flux model subject to stretch surface

    • Authors: SU Rehman, N Fatima, B Ali, M Imran, L Ali, NA Shah, JD Chung
    • Year: 2022
    • Citations: 72
    • Source: Mathematics, 10(16), 2877

  • Title: MHD Williamson nanofluid flow over a slender elastic sheet of irregular thickness in the presence of bioconvection

    • Authors: F Wang, MI Asjad, SU Rehman, B Ali, S Hussain, TN Gia, T Muhammad
    • Year: 2021
    • Citations: 63
    • Source: Nanomaterials, 11(9), 2297

  • Title: Significance of dust particles, nanoparticles radius, Coriolis and Lorentz forces: The case of Maxwell dusty fluid

    • Authors: Y Wei, SU Rehman, N Fatima, B Ali, L Ali, JD Chung, NA Shah
    • Year: 2022
    • Citations: 36
    • Source: Nanomaterials, 12(9), 1512

  • Title: Computational analysis for bioconvection of microorganisms in Prandtl nanofluid Darcy–Forchheimer flow across an inclined sheet

    • Authors: J Wang, Z Mustafa, I Siddique, M Ajmal, MMM Jaradat, SU Rehman, B Ali, et al.
    • Year: 2022
    • Citations: 23
    • Source: Nanomaterials, 12(11), 1791

  • Title: First solution of fractional bioconvection with power law kernel for a vertical surface

    • Authors: MI Asjad, S Ur Rehman, A Ahmadian, S Salahshour, M Salimi
    • Year: 2021
    • Citations: 18
    • Source: Mathematics, 9(12), 1366

  • Title: Dynamics of Eyring–Powell nanofluids when bioconvection and Lorentz forces are significant: The case of a slender elastic sheet of variable thickness with porous medium

    • Authors: A Manan, SU Rehman, N Fatima, M Imran, B Ali, NA Shah, JD Chung
    • Year: 2022
    • Citations: 13
    • Source: Mathematics, 10(17), 3039

  • Title: Hydrodynamical study of couple stress fluid flow in a linearly permeable rectangular channel subject to Darcy porous medium and no-slip boundary conditions

    • Authors: M Ishaq, SU Rehman, MB Riaz, M Zahid
    • Year: 2024
    • Citations: 10
    • Source: Alexandria Engineering Journal, 91, 50-69

 

liang cao | Interdisciplinary Mathematics | Best Researcher Award

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Dr. liang cao | Interdisciplinary Mathematics | Best Researcher Award

lecturer at Hunan Institute of Engineering, China 

Dr. Liang Cao, a faculty member at the Hunan Institute of Engineering, specializes in reliability analysis, wind energy technology, and advanced manufacturing. With a strong academic foundation from Xiangtan University, he has led funded research projects, including one supported by the Natural Science Foundation of Hunan Province. His contributions to structural reliability analysis include developing machine learning-based surrogate models for evaluating low failure probabilities, advancing computational efficiency in engineering. He has published in high-impact journals such as Smart Materials and Structures and Probabilistic Engineering Mechanics and holds multiple patents in mechanical engineering. A member of the Society of Mechanical Engineering, Dr. Cao’s research significantly impacts reliability-based design optimization, particularly in wind turbine gearboxes and robotic mechanisms. While his academic influence is growing, enhancing citation impact, industry collaborations, and editorial leadership could further strengthen his profile. His work continues to shape advancements in probabilistic mechanics and reliability engineering.

Professional Profile 

Scopus Profile
ORCID Profile

Education 

Dr. Liang Cao obtained his academic training from Xiangtan University, where he specialized in mechanical engineering. His education provided a strong foundation in reliability analysis, wind energy technology, and advanced manufacturing. During his academic journey, he gained expertise in probabilistic mechanics, structural safety, and optimization techniques, which later became the focus of his research. His studies emphasized the integration of computational modeling and experimental methods, equipping him with the skills necessary for advancing engineering reliability. Through coursework and research projects, he developed a deep understanding of mechanical system optimization, particularly in developing surrogate models for evaluating failure probabilities. His education laid the groundwork for his career in academia, where he continues to apply theoretical and computational approaches to improve structural and mechanical reliability. With a commitment to academic excellence, Dr. Cao remains engaged in continuous learning and professional development to further enhance his contributions to the field.

Professional Experience 

Dr. Liang Cao serves as a faculty member at the Hunan Institute of Engineering, where he contributes to teaching and research in mechanical engineering. His expertise in reliability analysis and design optimization has enabled him to guide students and researchers in developing innovative solutions for mechanical system reliability. Over the years, he has successfully led projects funded by the Natural Science Foundation of Hunan Province, further solidifying his reputation as an expert in the field. His work integrates computational modeling, machine learning, and structural safety to improve the performance of mechanical systems, particularly in wind turbine gearboxes and robotic mechanisms. Beyond research, he is actively involved in mentoring students and collaborating with peers to advance mechanical engineering methodologies. While he has made significant strides in academia, expanding his industry collaborations and assuming editorial or leadership roles would further strengthen his professional influence and contributions to the field.

Research Interest

Dr. Liang Cao’s research focuses on reliability analysis, probabilistic mechanics, and structural optimization in mechanical engineering. His work integrates machine learning techniques with reliability-based design optimization to improve the efficiency and accuracy of failure predictions. A key aspect of his research is the development of surrogate models, such as Radial Basis Function Neural Networks (RBFNN), for evaluating low failure probabilities with enhanced computational efficiency. His studies have direct applications in wind turbine gearboxes, robotic mechanisms, and piezoelectric dispensing systems, contributing to safer and more robust mechanical designs. Additionally, he explores multi-source uncertainty modeling to enhance structural reliability under variable conditions. His research is published in high-impact journals such as Smart Materials and Structures and Probabilistic Engineering Mechanics. Moving forward, expanding interdisciplinary collaborations and securing larger research grants could amplify the impact of his work on global mechanical engineering challenges.

Awards and Honors 

Dr. Liang Cao has received recognition for his contributions to mechanical engineering, particularly in reliability analysis and probabilistic mechanics. His research achievements have been supported by the Natural Science Foundation of Hunan Province, which funded his work on sliding bearing lubrication reliability in fan gearboxes. Additionally, his multiple patents reflect his innovative contributions to structural safety and optimization in mechanical systems. While he has gained credibility through journal publications in esteemed outlets such as Probabilistic Engineering Mechanics and Smart Materials and Structures, broader recognition through industry awards and professional society honors could further elevate his profile. Active participation in international research collaborations and engineering awards may increase his chances of securing prestigious research awards. By continuing to contribute to mechanical engineering advancements, Dr. Cao has the potential to earn more accolades, further solidifying his standing as a leading researcher in reliability engineering and mechanical system optimization.

Conclusion 

Dr. Liang Cao is an accomplished researcher in mechanical engineering, specializing in reliability analysis, probabilistic mechanics, and structural optimization. With a strong educational foundation from Xiangtan University and professional experience at the Hunan Institute of Engineering, he has made significant contributions to enhancing mechanical system safety and efficiency. His research, funded by the Natural Science Foundation of Hunan Province, has led to innovative developments in surrogate modeling and uncertainty analysis. He has published extensively in high-impact journals and holds multiple patents, reflecting his commitment to advancing engineering methodologies. While his academic impact is commendable, expanding his industry collaborations, citation influence, and leadership roles in research communities could further enhance his professional standing. With a growing reputation in reliability engineering, Dr. Cao is poised to make even greater contributions to mechanical system design and optimization, positioning himself as a leading figure in applied engineering research.

Publications Top Noted

  • Title: Optimizing Dispensing Performance of Needle-Type Piezoelectric Jet Dispensers: A Novel Drive Waveform Approach
    Authors: Liang Cao, S.G. Gong, Y.R. Tao, S.Y. Duan
    Year: 2024
    Source: Smart Materials and Structures

  • Title: Theoretical Study and Physical Tests on the Influence of Process Parameters of Needle on Dispensing Quality
    Authors: Liang Cao, S.G. Gong, S.Y. Duan, Y.R. Tao
    Year: 2023
    Source: Optik

  • Title: A RBFNN Based Active Learning Surrogate Model for Evaluating Low Failure Probability in Reliability Analysis
    Authors: Liang Cao, S.G. Gong, Y.R. Tao, S.Y. Duan
    Year: 2023
    Source: Probabilistic Engineering Mechanics

  • Title: Optimisation Design for Wind Turbine Mainshaft Bearing Based on Lubrication Reliability
    Authors: Liang Cao
    Year: 2020
    Source: International Journal of Reliability and Safety

  • Title: A Novel Evidence-Based Fuzzy Reliability Analysis Method for Structures
    Authors: Liang Cao
    Year: 2017
    Source: Structural and Multidisciplinary Optimization

  • Title: Safety Analysis of Structures with Probability and Evidence Theory
    Authors: Liang Cao
    Year: 2016
    Source: International Journal of Steel Structures