yanan Camaraza-Medina | Integracion Numerica | Editorial Board Member

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Dr. yanan Camaraza-Medina | Integracion Numerica | Editorial Board Member

Postdoctoral Research | University of Guanajuato | Mexico

Yanan Camaraza Medina is a mechanical engineer with 15 years of experience in thermal and energy systems, specializing in convective heat transfer, thermal radiation, and industrial heat-transfer equipment. His work integrates experimental, analytical, and numerical methods to improve the performance, safety, and efficiency of thermal systems used in energy generation and industrial applications. With academic and industrial expertise, he has served as a department head in thermal engineering, university professor, and researcher, contributing to advancements in thermophysical property modeling, phase-change processes, and multiphysics simulations. His research includes the development of predictive correlations, heat-transfer models, and computational strategies applied to real-world engineering problems.

Profiles: Scopus | Orcid 

Featured Publications

Camaraza Medina, Y. (2025). Proximate and ultimate analysis, higher heating value and inorganic chemical composition of woods from central region of Cuba. Sustainable Chemistry One World.

Camaraza Medina, Y., et al. (2025). Heat transfer modeling during condensation inside tubes with arbitrary geometrical orientations. Heat Transfer.

Camaraza Medina, Y. (2025). Experimental correlation of the steel’s thermophysical properties for thermal engineering applications. Heat Transfer.

Camaraza Medina, Y., et al. (2025). Multiphysics analysis of electric arc extinction in low voltage switchgear: Electromagnetic, thermal, and fluid dynamics interactions. Thermal Science and Engineering Progress.

Camaraza Medina, Y., et al. (2025). Analysis of transient heat conduction in tubes under convective boundary conditions. Heat Transfer.

Raghavendran Prabakaran | Fractional Differential Equations | Best Researcher Award

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Dr. Raghavendran Prabakaran | Fractional Differential Equations | Best Researcher Award

Researcher | Vel Tech Rangarajan Dr. Sagunthala R\&D Institute of Science and Technology | India

Dr. Raghavendran Prabakaran is an emerging mathematician specializing in fractional differential equations, integral transforms, control theory, and their applications in artificial intelligence and cryptography. With over 60 research contributions, including SCI and Scopus-indexed journal papers, conference presentations, book chapters, and patents, his work demonstrates both theoretical depth and applied innovation. His research focuses on the development and analysis of mathematical models for complex systems, emphasizing existence, stability, and controllability results in fractional calculus. Through rigorous analytical approaches and novel transform methods, Dr. Raghavendran advances the understanding of fractional integro-differential systems, contributing to both pure and applied mathematics. His growing citation impact across Scopus, Web of Science, and Google Scholar reflects his rising influence in computational and applied mathematical research.

Profiles: Scopus | Orcid | Google Scholar 

Featured Publications

Raghavendran, P., Gunasekar, T., Balasundaram, H., Santra, S. S., & Baleanu, D. (2024). Solving fractional integro-differential equations by Aboodh transform. Journal of Mathematics and Computer Science, 34, —. Citation count: 34.

Gunasekar, T., Raghavendran, P., Santra, S. S., & Sajid, M. (2024). Existence and controllability results for neutral fractional Volterra–Fredholm integro-differential equations. Journal of Mathematics and Computer Science, 34(4), 361–380. Citation count: 33.

Gunasekar, T., Raghavendran, P., Santra, S. S., & Sajid, M. (2024). Analyzing existence, uniqueness, and stability of neutral fractional Volterra–Fredholm integro-differential equations. Journal of Mathematics and Computer Science, 33(4), 390–407. Citation count: 29.

Gunasekar, T., Raghavendran, P., Santra, S. S., Majumder, D., & Baleanu, D. (2024). Application of Laplace transform to solve fractional integro-differential equations. Journal of Mathematics and Computer Science, 33(3), 225–237. Citation count: 26.

Gunasekar, T., & Raghavendran, P. (2024). The Mohand transform approach to fractional integro-differential equations. Journal of Computational Analysis and Applications, 33(1), 358–371. Citation count: 25.

Ajay Kumar | Numerical Analysis | Indian Institute of Technology Kanpur

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Dr. Ajay Kumar | Numerical Analysis | Indian Institute of Technology Kanpur

Post Doctoral | Indian Institute of Technology Kanpur | India

Dr. Ajay Kumar is a Postdoctoral Fellow in the Department of Mathematics and Statistics at the Indian Institute of Technology Kanpur, specializing in fractional calculus, nonlinear dynamics, numerical analysis, and mathematical modeling of disease and ecological systems. He earned his Ph.D. in Mathematics with a focus on fractional calculus from the National Institute of Technology Jamshedpur, following an M.Sc.-Tech in Mathematics and Computing from Jamia Millia Islamia and a B.Sc. in Physics, Chemistry, and Mathematics from CCS University, Meerut. Before joining IIT Kanpur, he served as an Assistant Professor at JECRC University, Jaipur, where he contributed to academic instruction and research mentorship. Dr. Kumar has an impressive publication record in high-impact journals such as Chaos, Solitons & Fractals, Results in Physics, Mathematics and Computers in Simulation, and Journal of Computational Science, reflecting his strong engagement in the study of fractional-order dynamical systems, eco-epidemiological modeling, and chaos theory. His research collaborations span internationally with scholars from Saudi Arabia, Egypt, and India, demonstrating a broad and interdisciplinary research network. He has also presented his work at multiple national and international conferences and participated in workshops and training programs that enhance computational and analytical expertise. Dr. Kumar’s academic excellence is supported by national-level qualifications such as GATE and IIT-JAM, alongside prestigious research fellowships including the Junior and Senior Research Fellowships from NIT Jamshedpur. With over 500 citations and an H-index of 10, his contributions significantly advance the application of fractional calculus in complex system modeling.

Profiles: ORCID | Google Scholar

Featured Publications

1. Kumar S., Kumar A., Samet B., Gómez-Aguilar J.F., Osman M.S., A chaos study of tumor and effector cells in fractional tumor-immune model for cancer treatment. Chaos, Solitons & Fractals, 2020, Citations: 222.

2. Kumar S., Kumar A., Samet B., Dutta H., A study on fractional host–parasitoid population dynamical model to describe insect species. Numerical Methods for Partial Differential Equations, 2021, Citations: 187.

3. Kumar A., Kumar S., A study on eco-epidemiological model with fractional operators. Chaos, Solitons & Fractals, 2022, Citations: 43.

4. Kumar S., Kumar A., Jleli M., A numerical analysis for fractional model of the spread of pests in tea plants. Numerical Methods for Partial Differential Equations, 2022, Citations: 27.

5. Alzaid S.S., Kumar A., Kumar S., Alkahtani B.S.T., Chaotic behavior of financial dynamical system with generalized fractional operator. Fractals, 2023, Citations: 18.

Mandli Rami Reddy | Mathematical Engineering | India

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Assist. Prof. Dr. Mandli Rami Reddy | Mathematical Engineering | India

Assistant Professor at Srinivasa Ramanujan Institute of Technology, India

Assist. Prof. Dr. Mandli Rami Reddy is a distinguished academic and researcher with over 18 years of teaching and research experience in Electronics and Communication Engineering, specializing in Wireless Sensor Networks, Wireless Communications, and IoT. He earned his B.Tech from SVCET, M.Tech in Communication and Signal Processing from GPREC, and is currently pursuing his Ph.D. at JNTUA, Anantapur. He has published numerous impactful papers in SCIE and Scopus-indexed journals and international conferences, along with four published patents in advanced wireless, AI, and IoT technologies. Beyond research, he actively contributes as a reviewer for reputed journals and is a life member of professional bodies including ISTE, IE(I), and IETE. His innovative research, academic leadership, and community involvement mark him as a promising scholar with strong future potential.

Professional Profile

Google Scholar | ORCID Profile 

Education

Assist. Prof. Dr. Mandli Rami Reddy has pursued a strong academic foundation in Electronics and Communication Engineering. He completed his Bachelor of Technology (B.Tech) in Electronics and Communication Engineering from SVCET, Chittoor, affiliated with JNTU Hyderabad. He later obtained his Master of Technology (M.Tech) in Communication and Signal Processing from GPREC, Kurnool, Andhra Pradesh. With a strong interest in advanced research, he is currently pursuing his Ph.D. at Jawaharlal Nehru Technological University Anantapur (JNTUA), Andhra Pradesh, India. His academic journey reflects a continuous pursuit of knowledge and innovation, with a focus on wireless sensor networks and communication systems. His educational background equips him with both theoretical expertise and practical insights into the evolving field of communication engineering, laying the groundwork for impactful research and teaching contributions.

Experience

Dr. Mandli Rami Reddy has more than eighteen years of academic and research experience, primarily as an Assistant Professor in Electronics and Communication Engineering. Over the years, he has served in several reputed engineering institutions across Andhra Pradesh and Telangana before joining Srinivasa Ramanujan Institute of Technology, Anantapur, where he continues to contribute actively. His teaching spans a wide range of subjects in communication and electronics, nurturing young engineers with strong technical skills and research-oriented thinking. With his expertise, he has mentored students in academic projects, research publications, and technology-driven innovations. In addition to teaching, he has established himself as a productive researcher with a series of published papers, patents, and international collaborations, thus balancing both academic and professional contributions effectively throughout his career.

Research Interest

The primary research interests of Dr. Mandli Rami Reddy focus on Wireless Sensor Networks, Wireless Communications, and Internet of Things (IoT). His studies emphasize enhancing localization techniques, improving network coverage, and optimizing energy efficiency in sensor networks using advanced algorithms. He has applied methods such as Particle Swarm Optimization, Genetic Algorithms, and Grey Wolf Optimization to develop robust solutions for network performance challenges. Furthermore, his research extends to the design of intelligent IoT devices, AI-based tools for optical communication, and sustainable applications like smart waste management systems. His publications in leading SCIE and Scopus-indexed journals demonstrate his commitment to addressing real-world technological issues. Through these research pursuits, he aims to contribute solutions that not only advance the field of communication engineering but also benefit industrial applications and societal needs.

Award and Honor

Throughout his career, Dr. Mandli Rami Reddy has been recognized for his contributions to research and academia. He has successfully published four patents in areas spanning wireless sensor networks, AI-based communication devices, and IoT-driven applications, demonstrating his innovation and problem-solving abilities. His academic publications in prestigious journals such as Applied Sciences, Wireless Networks, Computers, and SN Computer Science reflect his scholarly impact. He also contributes as a reviewer for reputed journals like the American Journal of Applied Scientific Research, showcasing his professional recognition within the research community. In addition, his memberships with professional organizations such as ISTE, IEI, IETE, IAENG, and SDIWC highlight his active engagement in professional networks. These honors collectively underline his dedication, innovation, and leadership in engineering research and education.

Research Skill

Dr. Mandli Rami Reddy possesses diverse research skills spanning algorithm development, wireless network optimization, and IoT device innovation. His expertise lies in improving accuracy in localization algorithms such as DV-Hop by integrating metaheuristic techniques including Particle Swarm Optimization and Genetic Algorithms. He has also worked extensively on energy-efficient protocols for wireless networks and smart device integration for sustainable applications. His ability to file patents demonstrates not only research competence but also practical application of technology to real-world challenges. Proficiency in academic writing, data analysis, and project execution further strengthen his profile as a capable researcher. Additionally, his collaborative approach and reviewing experience enhance his ability to critically assess and contribute to the scientific community. These combined skills enable him to create impactful and innovative research outcomes with academic and industrial relevance.

Publication Top Notes

  • Title: Energy-Efficient Cluster Head Selection in Wireless Sensor Networks Using an Improved Grey Wolf Optimization Algorithm
    Authors: M. R. Reddy, M. L. R. Chandra, P. Venkatramana, R. Dilli
    Year: 2023
    Citations: 122

  • Title: High Speed, Low Matchline Voltage Swing and Search Line Activity TCAM Cell Array Design in 14 nm FinFET Technology
    Authors: Ravindra Kumar
    Year: 2020
    Citations: 9*

  • Title: An improved 3D-DV-hop localization algorithm to improve accuracy for 3D wireless sensor networks
    Authors: M. R. Reddy, M. L. R. Chandra
    Year: 2024
    Citations: 5

  • Title: An enhanced 3D-DV-hop localisation algorithm for 3D wireless sensor networks
    Authors: M. R. Reddy, M. L. Ravi Chandra
    Year: 2024
    Citations: 3

  • Title: System Identification Using an Affine Combination of Two LMS Adaptive Filters
    Authors: P. Nagarjuna, M. Rami Reddy
    Year: 2012
    Citations: 1

  • Title: Enhanced Cuckoo Search Optimization with Opposition-Based Learning for the Optimal Placement of Sensor Nodes and Enhanced Network Coverage in Wireless Sensor Networks
    Authors: M. R. Reddy, M. L. R. Chandra, R. Dilli
    Year: 2025

  • Title: A Simplified Approach of Correlated Rician Fading Channel Estimation in Multi-User Ultra-Massive MIMO RIS-assisted Narrow Band Wireless Systems
    Authors: R. R. Mandli, M. L. R. Chandra, R. Dilli
    Year: 2024

  • Title: Optimal Node Deployment and Coverage in Next Generation Wireless Sensor Networks Applications
    Authors: R. R. Mandli, M. L. R. Chandra, R. Dilli
    Year: 2024

  • Title: Gaussian-Newton Localization Through Multilateration Algorithm for Wireless Sensor Networks
    Authors: M. R. Reddy, M. L. R. Chandra
    Year: 2023

  • Title: Design of 6G Communication System at THz Frequency Bands
    Authors: R. Dilli, R. C. M. L., R. R. Mandli
    Year: 2021

  • Title: Optimization Algorithm for Noise Cancellation Using Adaptive Estimator
    Authors: T. K. P. Mandli Rami Reddy, C. Thippeswamy
    Year: 2020

  • Title: A Nature Based Computing Technique for Image Watermarking using Bacterial Foraging Optimization, Wavelet and Cosine Transform
    Authors: M. L. R. C. Alam Siva Sankar, Mandli Rami Reddy
    Year: 2020

Conclusion

Assist. Prof. Dr. Mandli Rami Reddy stands out as a dedicated academician, researcher, and innovator with nearly two decades of impactful contributions in teaching and research. His educational background, research achievements, patents, and professional involvement position him as a strong contributor to the fields of communication engineering and IoT. With publications in reputed journals, successful patents, and active participation in professional societies, he continues to inspire students and peers alike. His balanced expertise in both theory and application reflects his commitment to bridging academic research with practical innovations. Looking ahead, his strong foundation, research skills, and leadership potential will enable him to expand international collaborations, publish in top-tier journals, and contribute further to advancing technology and benefiting society.

Sedaghat Shahmorad Moghanlou | Applied Mathematics | Best Researcher Award

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Prof. Sedaghat Shahmorad Moghanlou | Applied Mathematics | Best Researcher Award

Applied Math. Department at University of Tabriz, Iran

Prof. Sedaghat Shahmorad 🎓, a distinguished scholar in Applied Mathematics at the University of Tabriz 🇮🇷, specializes in numerical analysis, particularly integro-differential equations. With over two decades of academic experience 🧠, he has significantly contributed to the field through extensive teaching, research, and leadership. He has supervised numerous M.Sc. and Ph.D. theses 🎓📚 and authored multiple scholarly books and impactful journal articles 📖📝. His work on the Tau method and approximation techniques has earned recognition in computational mathematics 🧮. As Head of the Applied Mathematics Department and former Dean, he has demonstrated strong administrative and academic leadership 👨‍🏫📊. Prof. Shahmorad’s dedication to advancing numerical methods and mentoring future mathematicians makes him a highly deserving candidate for the Best Researcher Award 🏆🔬.

Professional Profile 

Education 🎓📘

Prof. Sedaghat Shahmorad earned his B.Sc. in Applied Mathematics from the University of Tabriz 🇮🇷, followed by an M.Sc. and Ph.D. in Numerical Analysis from the same institution. His academic journey has been marked by excellence in mathematical modeling and computational theory 📊. With a solid foundation in numerical methods and integro-differential equations, he developed deep expertise in solving complex mathematical problems 💡. Throughout his academic training, Prof. Shahmorad received high honors, standing out for his analytical acumen and innovation 🧠. His commitment to lifelong learning and scholarly development has shaped a distinguished academic and research career, reinforcing his role as a leading expert in numerical mathematics 📐🔍.

Professional Experience 👨‍🏫🏢

Prof. Shahmorad brings over two decades of academic and leadership experience in Applied Mathematics at the University of Tabriz 🎓. He has served as the Head of the Department of Applied Mathematics and formerly as the Dean of the Faculty of Mathematical Sciences 🏛️. In addition to his teaching duties, he has led multiple research projects, supervised numerous postgraduate students, and contributed to curriculum development 📚. His strong leadership and mentorship have made a lasting impact on the academic community 👥. He has also participated in editorial boards, conferences, and international collaborations 🌐. His professional trajectory reflects his deep commitment to both teaching and research excellence, making him a vital contributor to the advancement of numerical mathematics 🔬📈.

Research Interest 🔍📐

Prof. Shahmorad’s research focuses on numerical analysis, especially the development of efficient methods for solving integro-differential and delay differential equations 🔢. He is renowned for his work on Tau methods, spectral techniques, and high-order approximation algorithms, which have broad applications in engineering, physics, and applied sciences ⚙️🌌. His studies aim to bridge theoretical rigor with computational feasibility, providing tools for real-world problem-solving 💻📊. He also explores fractional calculus, integral transforms, and mathematical modeling of dynamic systems. His interdisciplinary research contributes significantly to advancing both applied and pure mathematical domains 📘🧪. Prof. Shahmorad’s innovative methodologies continue to influence emerging trends in computational mathematics and inspire the next generation of researchers around the globe 🌍.

Award and Honor 🏆🎖️

Prof. Sedaghat Shahmorad has received multiple awards and honors recognizing his academic excellence, innovative research, and outstanding mentorship 🏅📚. Notably, he has been acknowledged as a Top Researcher at the University of Tabriz and by national science organizations in Iran 🇮🇷. His contributions to numerical mathematics, especially in solving integro-differential equations, have earned accolades from peer-reviewed journals and international conference bodies 🧾🌟. He has also received honors for excellence in teaching and student supervision, highlighting his role as a mentor par excellence 👨‍🏫🌱. These awards are a testament to his impactful research output, dedication to knowledge dissemination, and continued service to the academic community 🎓🧠.

Research Skill 🧠💻

Prof. Shahmorad possesses advanced skills in mathematical modeling, numerical simulations, and algorithm development. He is proficient in implementing spectral and collocation methods, particularly the Tau method, to tackle complex integro-differential systems with precision 🔢📈. His expertise extends to fractional differential equations, delay systems, and applied analysis using computational tools like MATLAB and Mathematica 🖥️⚙️. With a strong command over linear algebra, integral transforms, and functional analysis, he develops robust algorithms that are widely cited and applied in science and engineering 🔍📚. His problem-solving approach blends theoretical insight with computational strategy, fostering innovation and practical applications in numerical mathematics 📘🚀.

Publications Top Note 📝

  • Title: Solving a class of auto-convolution Volterra integral equations via differential transform method
    Authors: Sedaghat Shahmorad, et al.
    Year: 2025
    Source: Journal of Mathematical Modeling

  • Title: Approximate solution of multi-term fractional differential equations via a block-by-block method
    Authors: Sedaghat Shahmorad, et al.
    Year: 2025
    Citations: 1
    Source: Journal of Computational and Applied Mathematics

  • Title: Convergence analysis of Jacobi spectral tau-collocation method in solving a system of weakly singular Volterra integral equations
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Citations: 1
    Source: Mathematics and Computers in Simulation

  • Title: Theoretical and numerical analysis of a first-kind linear Volterra functional integral equation with weakly singular kernel and vanishing delay
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Citations: 1
    Source: Numerical Algorithms

  • Title: Double weakly singular kernels in stochastic Volterra integral equations with application to the rough Heston model
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Source: Applied Mathematics and Computation

  • Title: Existence, uniqueness and blow-up of solutions for generalized auto-convolution Volterra integral equations
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Source: Applied Mathematics and Computation

  • Title: The application of fuzzy transform method to the initial value problems of linear differential–algebraic equations
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Source: Mathematical Sciences

  • Title: Solving fractional differential equations using cubic Hermit spline functions
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Source: Filomat (Open Access)

  • Title: Solving 2D-integro-differential problems with nonlocal boundary conditions via a matrix formulated approach
    Authors: Sedaghat Shahmorad, et al.
    Year: 2023
    Citations: 1
    Source: Mathematics and Computers in Simulation

  • Title: Review of recursive and operational approaches of the Tau method with a new extension
    Authors: Sedaghat Shahmorad, et al.
    Year: 2023
    Source: Computational and Applied Mathematics

Conclusion ✨📜

Prof. Sedaghat Shahmorad stands as a prominent figure in numerical analysis, combining deep theoretical knowledge with computational expertise 🌐📊. His dedication to teaching, mentoring, and advancing numerical methodologies has significantly shaped the field and inspired scholars across disciplines 🧠🎓. With a rich portfolio of research, leadership roles, and academic honors, he exemplifies excellence in mathematics and its real-world applications 🧾🏅. His work not only contributes to scientific understanding but also provides tools for innovation across technology and engineering sectors 🧬⚙️. As a visionary academic and skilled researcher, Prof. Shahmorad continues to influence future directions in computational and applied mathematics with distinction 🌟📘.

Claudia Pacurar | Mathematical Engineering | Best Researcher Award

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Prof. Dr. Claudia Pacurar | Mathematical Engineering | Best Researcher Award

Professor/Director at Technical University of Cluj-Napoca, Romania

Professor Claudia Păcurar 🎓, a distinguished academic at the Technical University of Cluj-Napoca 🇷🇴, is a trailblazer in electrical engineering ⚡. With over two decades of experience in academia, she has progressed from assistant professor to full professor, demonstrating exemplary leadership 📘. Her research spans electromagnetic field modeling, spiral inductors, wireless power transfer, and antenna design 📡. She has authored 7 books 📚 and over 150 scientific papers, including 57 ISI-indexed works, showcasing her dedication to innovation and scientific excellence 🧠. Fluent in multiple languages 🌍 and a skilled communicator, she actively contributes to national and international conferences and research projects 🌐. Her technical acumen, organizational finesse, and commitment to student success make her a respected mentor and influential scholar 👩‍🏫. With a visionary focus on advanced electrotechnics and practical applications, Professor Păcurar continues to shape the future of engineering education and research 🔬🚀.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

🎓 Education

Professor Claudia Păcurar’s academic path reflects a lifelong devotion to mastering the intricacies of electrical engineering and applied sciences. She earned her undergraduate degree from the Technical University of Cluj-Napoca in 2001, followed by a PhD in Electrical Engineering in 2008 with a thesis on micrometer spiral inductors 🔁. Her commitment to scholarly advancement led her to earn the prestigious Habilitation Degree in 2022, a milestone that reflects her qualification to mentor doctoral students and lead pioneering research. Throughout her educational trajectory, she has balanced foundational theory with practical innovation, combining mathematics 🧮, electromagnetism 🌐, and computational design into a cohesive and forward-thinking academic philosophy. Her deep understanding of electromagnetic systems and smart technologies has laid a firm foundation for a transformative career in academia, innovation, and engineering leadership 🚀.

👩‍💼 Professional Experience

Professor Păcurar has steadily ascended the academic ranks at the Technical University of Cluj-Napoca, demonstrating versatility, vision, and value. Since joining in 2001 as a teaching assistant, she progressed to Lecturer, then Associate Professor, and ultimately became a Full Professor in 2022 🏛️. Her administrative roles—including  Director of the Alumni Department—highlight her ability to harmonize academic excellence with institutional strategy and student engagement 🎯. She has served as a project manager, course coordinator, and technical organizer for international conferences, showcasing her multifaceted expertise and leadership capabilities 🔧. Beyond lectures and laboratories, she has mentored countless students, led educational initiatives, and co-developed cutting-edge software for electromagnetic design tools 💻. Professor Păcurar’s professional trajectory embodies dedication to teaching, research, and engineering advancement, underscoring her status as a pillar of the university and a prominent contributor to the broader scientific community 🌍.

🔬 Research Interest

Professor Păcurar’s research is rooted in the magnetic forces that power modern technologies and the numerical models that optimize them. Her interests center around electromagnetic field theory, the design and simulation of planar spiral inductors, antennas 📡, filters, and wireless power transfer systems ⚙️. A specialist in numerical modeling, she integrates advanced simulation methods with real-world engineering problems to craft innovative, energy-efficient solutions. Her work bridges the theoretical and the practical, often involving in-house software development such as CIBSOC and ABSIF for inductor optimization 💡. She explores nonlinear behavior, eddy currents, optimization algorithms, and smart system integration—all aligned with the growing demand for sustainable and intelligent electronics 🌱. Her interdisciplinary approach connects electronics, computer-aided design, and materials science, enabling her to address emerging challenges in telecommunication, medical devices, and energy systems with accuracy, elegance, and originality 🎇.

🏅 Awards and Honors

Professor Păcurar has earned well-deserved recognition for her academic and research accomplishments through numerous accolades. She was honored with the Diploma of Excellence by the Technical University of Cluj-Napoca for her substantial contributions to research, teaching, and university development 🎓. Her work has also received attention at national and international levels, evidenced by frequent invitations to serve as conference chair, reviewer, and program committee member across various global events 🌍. Her publications—especially those indexed by ISI and Scopus—have garnered citations and acclaim, confirming the high impact of her work 📖. Her dedication to educational excellence, innovation, and mentorship has made her a role model within the engineering faculty 👩‍🏫. These distinctions are not merely titles, but reflections of her continual drive to push scientific boundaries and inspire future generations of engineers and researchers 🔭.

 Conclusion

Professor Claudia Păcurar stands as a beacon of academic integrity, research innovation, and educational leadership. From her formative years as a scholar to her current stature as a full professor and institutional leader, she has consistently exemplified excellence, creativity, and service 👩‍🔬. Her interdisciplinary mindset, combined with technical precision and a passion for teaching, positions her at the forefront of electromagnetic and wireless systems research 📶. As an author, mentor, and software innovator, she has made a lasting impact on students, colleagues, and the scientific community alike. Her journey, defined by curiosity and achievement, continues to fuel advancements in engineering education and applied technology 🔋. Professor Păcurar is not just shaping circuits—she is shaping minds, systems, and the future of intelligent infrastructure with every line of code, formula, and lecture 💫.

Publications Top Notes

📘 Title: Inductance calculation and layout optimization for planar spiral inductors
Authors: C. Pacurar, V. Topa, A. Racasan, C. Munteanu
Year: 2012
Citations: 37
Source: 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), 2012

📘 Title: Studies of Inductance Variation for Square Spiral Inductors using CIBSOC Software
Authors: C. Pacurar, V. Topa, C. Munteanu, A. Racasan, C. Hebedean
Year: 2013
Citations: 30
Source: Environmental Engineering & Management Journal (EEMJ), Vol. 12, Issue 6

📘 Title: Minimization of the equivalent parallel capacitance in planar magnetic EMI filters
Authors: A. Racasan, C. Munteanu, V. Tapa, C. Pacurar, C. Hebedean
Year: 2012
Citations: 17
Source: International Conference and Exposition on Electrical and Power Engineering (EPE), 2012

📘 Title: Spiral inductors inductance computation and layout optimization
Authors: C. Păcurar, V. Ţopa, C. Munteanu, A. Racasan, C. Hebedean
Year: 2012
Citations: 15
Source: International Conference and Exposition on Electrical and Power Engineering (EPE), 2012

📘 Title: High frequency analysis and optimization of planar spiral inductors used in microelectronic circuits
Authors: C. Pacurar, V. Topa, A. Giurgiuman, C. Munteanu, C. Constantinescu, …
Year: 2021
Citations: 14
Source: Electronics, Vol. 10, Issue 23, Article 2897

📘 Title: High Frequency Analysis of the Vivaldi Antenna Parameters
Authors: C. Constantinescu, C. Munteanu, L. Grindei, A. Giurgiuman, C. Pacurar, …
Year: 2020
Citations: 3
Source: 2020 International Conference and Exposition on Electrical and Power Engineering

📘 Title: High gain improved planar Yagi Uda antenna for 2.4 GHz applications and its influence on human tissues
Authors: C. Constantinescu, C. Pacurar, A. Giurgiuman, C. Munteanu, S. Andreica, …
Year: 2023
Citations: 10
Source: Applied Sciences, Vol. 13, Issue 11, Article 6678

📘 Title: Application of Windings Shifting for the Optimization of Planar Structures
Authors: C. Hebedean, C. Munteanu, A. Racasan, C. Pacurar
Year: 2013
Citations: 10
Source: Environmental Engineering & Management Journal (EEMJ), Vol. 12, Issue 6

📘 Title: Filter geometry optimization for the conduction electromagnetic interferences suppression
Authors: A. Racasan, C. Munteanu, V. Topa, C. Pacurar, C. Hebedean
Year: 2014
Citations: 9
Source: 2014 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM)

📘 Title: Minimization of the equivalent parallel capacitance in planar magnetic integrated structures
Authors: A. Racasan, C. Munteanu, V. Topa, C. Pacurar, C. Hebedean
Year: 2012
Citations: 9
Source: 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), 2012

📘 Title: Optimum geometry for planar structures regarding their loss factor
Authors: C. Hebedean, C. Munteanu, R. Adina, C. Pacurar
Year: 2012
Citations: 9
Source: 7th International Conference and Exposition on Electrical and Power Engineering (EPE)

📘 Title: Advances on parasitic capacitance reduction of EMI filters
Authors: A. Racasan, C. Munteanu, V. Topa, C. Pacurar, C. Hebedean, S. Lup
Year: 2010
Citations: 9
Source: Annals of the University of Craiova, Electrical Engineering series

📘 Title: High frequency analysis of bowtie antennas
Authors: C. Constantinescu, C. Munteanu, C. Pacurar, A. Giurgiuman, M. Gliga, …
Year: 2019
Citations: 7
Source: 2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE)

📘 Title: Analysis, identification and minimization of the parasitic effects of the multilayer spiral inductors
Authors: A. Racasan, C. Munteanu, C. Pacurar, V. Topa, C. Constantinescu, F. Pop, …
Year: 2016
Citations: 7
Source: 2016 International Conference and Exposition on Electrical and Power Engineering (EPE)

📘 Title: The influence of parameters on the parasitic capacitance values in a planar transformer
Authors: C. Hebedean, C. Munteanu, A. Racasan, C. Pacurar, D. Augustin
Year: 2015
Citations: 7
Source: 2015 9th International Symposium on Advanced Topics in Electrical Engineering (ATEE)

📘 Title: Technologies to improve high frequency characteristics of integrated EMI filters
Authors: A. Racasan, C. Munteanu, V. Topa, C. Racasan, O. Antonescu
Year: 2007
Citations: 7
Source: 6th International Conference on Electromechanical and Power Systems, Chisinau

Michael Todinov | Mathematical Engineering | Best Researcher Award

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Prof. Michael Todinov | Mathematical Engineering | Best Researcher Award

Professor in Mechanical Engineering at Oxford Brookes University, School of Engineering, Computing and Mathematics, United Kingdom

Professor Michael Todinov is a trailblazing mind in the realm of applied mathematics, reliability engineering, and risk analysis 🌐📊. Renowned for his pioneering contributions to flow networks, reliability modeling, and probabilistic safety assessment, he has authored numerous influential papers and books that have reshaped contemporary engineering thinking 📘⚙️. With a unique approach that blends mathematical innovation with practical utility, Prof. Todinov has introduced novel methodologies for optimizing system performance under uncertainty and complexity 🔍🔧. His work is widely applied across infrastructure, manufacturing, and safety-critical systems, cementing his status as a visionary scholar and problem-solver 🏗️🧠. As a respected educator and thought leader, he continues to inspire a new generation of engineers and researchers to embrace analytical rigor with creative foresight 🎓💡. Driven by curiosity and excellence, Prof. Todinov’s legacy is a testament to the power of mathematical insight in transforming real-world systems 🌟📐.

Professional Profile

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🎓 Education

Prof. Michael Todinov’s educational journey 🌍 began with a First-Class Honours degree in Mechanical Engineering from the Technical University of Sofia 🎓, where his early fascination with precision and systems emerged. Driven by intellectual curiosity, he pursued a PhD at the University of Birmingham—an extraordinary accomplishment completed without formal supervision, based solely on published research 📚. Later, he earned a Doctor of Engineering (DEng), the UK’s equivalent of a DSc, for his pioneering work in probabilistic modeling and system reliability 🔍. This academic evolution reflects a rare synthesis of engineering insight ⚙️ and mathematical depth ➕, enabling him to approach challenges from a multidisciplinary perspective. His educational path has been marked by rigor, creativity, and trailblazing scholarship—qualities that continue to define his professional excellence today. 🧠

💼 Professional Experience

With over 30 years of experience 🌟, Prof. Todinov has held key roles across UK institutions, including his current position as Professor at Oxford Brookes University 🎓. Earlier, he led groundbreaking research as Head of Risk and Reliability at Cranfield University and served as a Research Scientist at the University of Birmingham 🧪. His professional journey blends academic excellence with real-world innovation 🌐, including collaborations with major organizations like BP, Total, and KIMM. His work spans failure modeling, flow network optimization, and engineering safety, using cutting-edge algorithms and simulation techniques 🧮. Whether developing industry solutions or mentoring PhD students 🎓, Prof. Todinov brings a unique fusion of creativity, logic, and leadership. His roles reflect a consistent dedication to advancing applied mathematics and making theory work in practice ⚒️.

🔬 Research Interests

Prof. Todinov’s research is a deep dive into the world of probability, optimization, and system reliability 🎯. He develops new theories and practical models that redefine how we assess risks and design safer, more efficient systems 💡. His focus areas include probabilistic risk reduction, algebraic inequalities, flow networks, and fracture mechanics 🧱. Notably, he challenged and corrected traditional reliability models 🔄, offering innovative alternatives with real-world impact. His algorithm for maximizing flow through damaged networks is the fastest known, making it vital for industries like energy ⚡ and infrastructure 🚧. He also introduced methods for reverse-engineering algebraic inequalities—a breakthrough in mathematical logic 🧠. Prof. Todinov’s work is both foundational and futuristic, balancing theoretical brilliance with powerful applications that influence global engineering and safety practices. 🔧

🏅 Awards and Honors

Prof. Todinov has been recognized globally for his exceptional work 🥇. He received honors from the Institution of Mechanical Engineers (UK) for his influential contributions to engineering risk reduction 🛡️. His Doctor of Engineering (DEng) was conferred in acknowledgment of his career-long breakthroughs in mathematical modeling, an award rarely granted and held by only a select few 🔝. His books—published by Wiley, Elsevier, and CRC Press—have become foundational references across academic and industrial communities 📖. He’s a frequent keynote speaker, journal editorial board member, and award-winning educator 🎤📘. His blend of academic impact and practical innovation has earned him international respect, with accolades that confirm his status as a pioneer in risk science and reliability engineering ⚙️. These honors reflect not just achievement, but lasting influence.

Conclusion

Prof. Michael Todinov stands as a brilliant example of how mathematics and engineering can shape real-world systems 🌐. His research has led to smarter designs, safer infrastructures, and more reliable systems worldwide 🛠️. By blending advanced theory with hands-on solutions, he’s redefined what it means to be an applied mathematician and engineer 🚀. Whether leading research, inspiring students 🎓, or developing the next breakthrough algorithm, his impact is wide-reaching and deeply rooted. As a thinker, educator, and innovator 💬, he’s left a legacy that transcends borders and disciplines. His work continues to elevate global standards in risk management, optimization, and system resilience, earning him a well-deserved place among the world’s top research minds 🧩. Prof. Todinov’s journey reminds us that the intersection of logic and creativity is where true innovation thrives. ✨

Publications Top Notes

📖 Title: Reverse Engineering of Algebraic Inequalities for System Reliability Predictions and Enhancing Processes in Engineering
✍️ Authors: M.T. Todinov, Michael Todorov
📅 Year: 2024
🔢 Citations: 7
📖 Source: IEEE Transactions on Reliability 📰

📖 Title: Lightweight Designs and Improving the Load-Bearing Capacity of Structures by the Method of Aggregation
✍️ Authors: M.T. Todinov, Michael Todorov
📅 Year: 2024
🔢 Citations: 1
📖 Source: Mathematics 📐

📖 Title: Enhancing the Reliability of Series-Parallel Systems With Multiple Redundancies by Using System-Reliability Inequalities
✍️ Authors: M.T. Todinov, Michael Todorov
📅 Year: 2023
🔢 Citations: 2
📖 Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering 🛠️

📖 Title: Reliability-Related Interpretations of Algebraic Inequalities
✍️ Authors: M.T. Todinov, Michael Todorov
📅 Year: 2023
🔢 Citations: 5
📖 Source: IEEE Transactions on Reliability 🔧

📖 Title: Probabilistic Interpretation of Algebraic Inequalities Related to Reliability and Risk
✍️ Authors: M.T. Todinov, Michael Todorov
📅 Year: 2023
🔢 Citations: 1
📖 Source: Quality and Reliability Engineering International 📊

📖 Title: Improving Reliability by Increasing the Level of Balancing and by Substitution
✍️ Authors: M.T. Todinov, Michael Todorov
📅 Year: 2023
🔢 Citations: 1
📖 Source: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science ⚙️

📖 Title: Can System Reliability Be Predicted from Average Component Reliabilities?
✍️ Authors: M.T. Todinov, Michael Todorov
📅 Year: 2023
🔢 Citations: 1
📖 Source: Safety and Reliability 🔒

📖 Title: Improving System Reliability and the Probability of Selecting Reliable Components by Interpreting Algebraic Inequalities
✍️ Authors: M.T. Todinov, Michael Todorov
📅 Year: 2023
📖 Source: International Journal of Modelling, Identification and Control 🎯

📖 Title: On the Use of Analytical Inequalities for Improving Reliability and Reducing Risk
✍️ Authors: M.T. Todinov, Michael Todorov
📅 Year: 2023
📖 Source: International Journal of Risk Assessment and Management ⚖️

📖 Title: Risk-based Reliability Analysis and Generic Principles for Risk Reduction
✍️ Authors: M.T. Todinov
📅 Year: 2006
🔢 Citations: 114
📖 Source: Elsevier 📈

📖 Title: On Some Limitations of the Johnson–Mehl–Avrami–Kolmogorov Equation
✍️ Authors: M.T. Todinov
📅 Year: 2000
🔢 Citations: 80
📖 Source: Acta Materialia 🧪

📖 Title: Necessary and Sufficient Condition for Additivity in the Sense of the Palmgren–Miner Rule
✍️ Authors: M.T. Todinov
📅 Year: 2001
🔢 Citations: 75
📖 Source: Computational Materials Science 🔬

📖 Title: Is Weibull Distribution the Correct Model for Predicting Probability of Failure Initiated by Non-Interacting Flaws?
✍️ Authors: M.T. Todinov
📅 Year: 2009
🔢 Citations: 58
📖 Source: International Journal of Solids and Structures 🏗️

📖 Title: Flow Networks: Analysis and Optimization of Repairable Flow Networks, Networks with Disturbed Flows, Static Flow Networks and Reliability Networks
✍️ Authors: M.T. Todinov
📅 Year: 2013
🔢 Citations: 54
📖 Source: Newnes 🌐

Sohail Ahmad Khan | Applied Mathematics | Young Scientist Award

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Dr. Sohail Ahmad Khan | Applied Mathematics | Young Scientist Award

Research Associate at Quaid I Azam University Islamabad, Pakistan

Dr. Sohail Ahmad Khan 🌍📘, a distinguished researcher from the Department of Mathematics at Quaid-i-Azam University, Islamabad, stands among the world’s Top 2% scientists as recognized by Stanford University 🌟📊. With a PhD in Applied Mathematics (2024) and over 127 ISI-indexed publications, his work in fluid mechanics and nanomaterial dynamics 💧🧪 has garnered global acclaim. Boasting an H-index of 30 and a cumulative impact factor exceeding 500 🔬📈, Dr. Khan is a prolific author and a dedicated reviewer for over 120 high-impact journals. His academic excellence has been honored with multiple international awards 🏅🌐, fellowships, and top-cited recognitions. As an organizer and contributor to major scientific forums, he consistently drives forward environmental and thermal engineering research 🌱🔥. Dr. Khan’s dedication, interdisciplinary expertise, and visionary leadership mark him as an outstanding contender for the Young Scientist Award 🏆🔍.

Professional Profile 

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Education 🎓📘

Dr. Sohail Ahmad Khan’s academic voyage began with a BSc in Mathematics & Physics from the University of Science and Technology, Bannu (2014), followed by an MSc (2017), MPhil (2019), and PhD in Applied Mathematics (2024) from Quaid-i-Azam University, Islamabad. His education reflects a deep-rooted passion for mathematical precision and applied problem-solving 🔍📐. Throughout his academic progression, Dr. Khan honed his expertise in fluid mechanics, nanomaterial dynamics, and nonlinear analysis, laying a solid foundation for a prolific research career. His consistent academic excellence earned him competitive fellowships at each level, reinforcing his stature as a devoted scholar. From foundational mechanics to advanced computational modeling, his scholastic path showcases an unwavering dedication to unraveling complex real-world phenomena through mathematical elegance 📊🔬.

Professional Experience 👨‍🏫💼

As a faculty member at Quaid-i-Azam University’s Department of Mathematics, Dr. Khan has played an instrumental role in shaping academic and research landscapes 🌐📚. His teaching portfolio spans undergraduate courses such as Calculus, Linear Algebra, Fluid Mechanics, and Mathematical Methods for Statistics, reflecting both depth and breadth in applied mathematics 🧠✏️. Beyond classroom instruction, he has actively participated in curriculum development, academic mentoring, and interdisciplinary collaboration. He’s also taken a leadership role in organizing several international conferences, promoting innovation and scholarly exchange across domains. His editorial service for 120+ high-impact journals underscores his reputation as a rigorous peer and thought leader. Dr. Khan’s professional engagements not only reflect his commitment to knowledge dissemination but also his pivotal role in nurturing the next generation of mathematicians and applied scientists 🌟📖.

Research Interests 🔬🧪

Dr. Sohail Ahmad Khan’s research pursuits orbit the intricate domains of fluid dynamics, nanomaterial science, thermal transport, and nonlinear partial differential equations 💧🌡️. His work primarily addresses real-world problems involving entropy generation, heat and mass transfer, magnetohydrodynamics, and radiative flow phenomena—topics critical to engineering, environmental science, and biophysics. His interdisciplinary flair merges applied mathematics with computational simulations, offering analytical solutions that bridge theory and practice 🧠💡. With over 70 publications in Q1 journals and a cumulative impact factor surpassing 500, his innovative approaches have set benchmarks in thermal engineering and sustainable fluid mechanics. Dr. Khan’s cutting-edge investigations not only advance mathematical frontiers but also contribute to addressing global challenges such as energy efficiency, climate impact, and biomedical transport systems 🌍💥.

Awards and Honors 🏅🌟

Dr. Khan’s excellence has been celebrated both nationally and internationally. Twice listed among the World’s Top 2% Scientists by Stanford University (2022, 2024) 🌍📊, he stands as a beacon of global impact. His accolades include the International Best Researcher Award, Young Scientist Award, and a prestigious Gold Medal for his PhD research in fluid mechanics 🥇🌀. He’s received the Chief Minister Education Endowment Scholarship, MPhil and PhD fellowships, and recognition for publishing top-cited articles in elite journals like ZAMM 📈📚. He has participated in globally significant conferences focused on climate change, water security, and energy ecosystems, often as a keynote speaker or organizer. These accolades underscore his scholarly brilliance, leadership, and sustained contribution to applied mathematical research. His honors not only validate his academic journey but inspire aspiring researchers to aim higher and pursue meaningful, high-impact inquiry 💫🔍.

Conclusion 🧾✅

Dr. Sohail Ahmad Khan exemplifies the spirit of innovation, academic rigor, and impactful research 🧠🏆. With a robust academic foundation, stellar research credentials, and numerous international accolades, he stands as an outstanding candidate for the Young Scientist Award. His influential work in applied mathematics, particularly fluid mechanics and nanomaterial modeling, addresses pressing scientific challenges and resonates across disciplines. Through mentoring, publication, and conference leadership, he continually uplifts the research ecosystem, both locally and globally 🌐📢. His remarkable scholarly output, collaborative ethos, and unwavering dedication to excellence position him not only as a formidable mathematician but also as a visionary leader in scientific advancement. In every dimension—education, research, service, and community engagement—Dr. Khan proves to be a paragon of academic excellence, richly deserving of recognition on the world stage 🏅🌍.

Publications Top Notes

🔬 TASA Formulation for Nonlinear Radiative Flow of Walter-B Nanoliquid Invoking Microorganism and Entropy Generation

Authors: T. Hayat, A. Razzaq, S.A. Khan, A. Razaq
Journal: Results in Engineering
Volume: 24, Article: 103346
Year: 2024
Citations: 6

☀️ Entropy Induced Flow Model for Solar Radiation Through Nanomaterials with Cubic Autocatalysis Reaction

Authors: A. Razaq, S.A. Khan, A. Alsaedi, T. Hayat
Journal: Journal of Magnetism and Magnetic Materials
Volume: 586, Article: 171172
Year: 2023
Citations: 6

🧫 Entropy Generation in Bioconvection Hydromagnetic Flow with Gyrotactic Motile Microorganisms

Authors: S.A. Khan, T. Hayat, A. Alsaedi
Journal: Nanoscale Advances
Volume: 5(18), Pages: 4863–4872
Year: 2023
Citations: 6

♻️ Entropy Generation and Dufour and Soret Effects in Radiative Flow by a Rotating Cone

Authors: S.A. Khan, T. Hayat, A. Alsaedi, S. Momani
Journal: Physica Scripta
Volume: 96(2), Article: 025209
Year: 2020
Citations: 6

🌡️ Entropy Generated Nonlinear Mixed Convective Beyond Constant Characteristics Nanomaterial Wedge Flow

Authors: A. Razaq, T. Hayat, S.A. Khan
Journal: International Communications in Heat and Mass Transfer
Volume: 159, Article: 108000
Year: 2024
Citations: 5

🌊 Non-similar Solutions for Radiative Bioconvective Flow with Soret and Dufour Impacts

Authors: M.W. Ahmad, T. Hayat, A. Alsaedi, S.A. Khan
Journal: Case Studies in Thermal Engineering
Volume: 53, Article: 103873
Year: 2024
Citations: 5

🔥 Thermal Energy Transport in Nanomaterial Flow with Modified Heat and Mass Transfer Laws

Authors: T. Hayat, A. Razaq, S.A. Khan, M.A. Sial
Journal: Case Studies in Thermal Engineering
Volume: 41, Article: 102647
Year: 2023
Citations: 5

💡 Radiative Bioconvective Walter-B Nanoliquid Flow with Soret and Dufour Effects

Authors: S.A. Khan, A. Razaq, T. Hayat, A. Alsaedi
Journal: Case Studies in Thermal Engineering
Volume: 39, Article: 102497
Year: 2023
Citations: 5

⚙️ Non-Newtonian Bioconvection in Sutterby Nanoliquid with Thermal Fluctuations and Radiation

Authors: T. Hayat, A. Razaq, S.A. Khan
Journal: Case Studies in Thermal Engineering
Volume: 37, Article: 102271
Year: 2022
Citations: 5

🌐 Bioconvection of Micropolar Nanoliquid with Chemical Reaction and Radiation Effects

Authors: S.A. Khan, A. Razaq, T. Hayat, A. Alsaedi
Journal: Journal of Materials Research and Technology
Volume: 23, Pages: 2889–2901
Year: 2023
Citations: 4

 ⚡ Entropy Generation in Reactive Nanofluid Flow with Frictional Heating and Magnetic Force

Authors: S.A. Khan, T. Hayat, A. Alsaedi
Journal: Physica Scripta
Volume: 96(2), Article: 025209
Year: 2020
Citations: 4

 🌀 Bioconvective Nanofluid Flow Through a Rotating Disk Under Joule Heating

Authors: T. Hayat, A. Alsaedi, S.A. Khan
Journal: Journal of Molecular Liquids
Volume: 324, Article: 114717
Year: 2021
Citations: 4

 💧 Analysis of Nanofluid Bioconvection in a Porous Medium with Joule Heating and Irreversibility

Authors: T. Hayat, S.A. Khan, A. Alsaedi
Journal: Journal of Molecular Liquids
Volume: 323, Article: 114617
Year: 2021
Citations: 4

 🧪 Bio-Convection of Micropolar Nanoliquid in a Porous Media with Thermophoresis and Soret Effects

Authors: S.A. Khan, A. Alsaedi, T. Hayat
Journal: Journal of Materials Research and Technology
Volume: 21, Pages: 2037–2047
Year: 2022
Citations: 3

 🔬 Entropy-Optimized Bio-Convective Flow of Nanofluid in a Porous Medium with Cattaneo–Christov Theory

Authors: T. Hayat, A. Alsaedi, S.A. Khan
Journal: International Journal of Heat and Mass Transfer
Volume: 180, Article: 121769
Year: 2021
Citations: 3

 🌡️ Heat Transfer Characteristics in Nanofluid Flow with Thermal Radiation and Activation Energy

Authors: S.A. Khan, A. Razaq, T. Hayat
Journal: Physica Scripta
Volume: 97(2), Article: 025213
Year: 2022
Citations: 3

 ⚗️ Micropolar Nanofluid Bioconvection Over a Stretching Sheet with Joule Heating and Chemical Reaction

Authors: S.A. Khan, T. Hayat, A. Alsaedi
Journal: Case Studies in Thermal Engineering
Volume: 31, Article: 101815
Year: 2022
Citations: 3

 🔥 Thermal Radiation and Magnetohydrodynamics in Bioconvective Nanofluid Flow Through Porous Media

Authors: S.A. Khan, A. Alsaedi, T. Hayat
Journal: Journal of Molecular Liquids
Volume: 337, Article: 116453
Year: 2021
Citations: 3

Chun Xu | Interdisciplinary Mathematics | Best Researcher Award

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Prof. Dr. Chun Xu | Interdisciplinary Mathematics | Best Researcher Award

Professor at Xinjiang University of Finance & Economics, China

Prof. Dr. Xu Chun 🎓, a distinguished scholar and PhD supervisor in the realm of Big Data Analysis and Applications 📊💡, exemplifies excellence in research and education. Earning his PhD from the University of Chinese Academy of Sciences in 2018, he has rapidly risen as a thought leader, recognized through the prestigious “Tianshan Talent” program 🌟. With over 40 impactful publications in leading journals 📚 and leadership of 13 major research projects, including those under the National Natural Science Foundation, Prof. Xu has significantly advanced data-driven innovation and technology. His accolades include top honors in national teaching and academic paper competitions 🏅, reflecting a rare fusion of pedagogical brilliance and scientific depth. Passionate about discovery, mentorship, and cross-disciplinary growth, he continues to inspire the scientific community with his visionary work and collaborative spirit 🤝. Prof. Xu Chun stands as a beacon of innovation, shaping the future of intelligent data applications.

Professional Profile 

Scopus Profile

🎓 Education

Prof. Dr. Xu Chun’s academic path is a story of dedication and precision. He earned his PhD in Computer Application Technology from the prestigious University of Chinese Academy of Sciences in 2018 🎓, laying a firm foundation in the ever-evolving domain of computational intelligence and big data. His education is steeped in rigorous analytical training, advanced machine learning, and algorithmic design. This academic odyssey empowered him with a multifaceted understanding of the data ecosystem—from raw datasets to real-world applications 📈. His scholarly journey reflects a commitment to lifelong learning, academic excellence, and technical innovation. With each milestone, Prof. Xu has cemented himself as a profound thinker, ready to tackle future challenges through a lens of scientific curiosity and intellectual precision 🧠🔍.

💼 Professional Experience

With an illustrious career marked by leadership and innovation, Prof. Xu Chun currently serves as a full Professor and PhD supervisor 🧑‍🏫. Over the years, he has cultivated an ecosystem of excellence in data science, guiding numerous doctoral students and researchers toward impactful academic and industry pursuits. He has successfully led 13 competitive projects including those from the National Natural Science Foundation, Xinjiang Aid Program, and the Xinjiang Natural Science Foundation 🔬💼. His professional experience combines high-stakes research management with grassroots mentorship, establishing him as a pillar of scholarly progress. Moreover, his role in academic development within the Xinjiang Uygur Autonomous Region has contributed significantly to regional scientific advancement 🧭. Prof. Xu is not only an academic leader but a visionary orchestrator of computational innovation—bridging institutional goals with the broader tech-research frontier. 🌐

🔬 Research Interest

Prof. Xu Chun’s research interests orbit around Big Data Analysis and Applications, an ever-expanding universe of digital insight 🚀📊. His work explores the convergence of algorithmic intelligence, machine learning, and large-scale data systems—striving to make sense of complexity through structured, meaningful interpretations. He delves into predictive analytics, pattern recognition, and intelligent computing, with a keen focus on real-world utility and interdisciplinary crossover 🌉. Xu’s research thrives on innovation—constantly pushing boundaries to unlock new knowledge and scalable solutions. Whether it’s optimizing data flow, improving data-driven decision-making, or constructing intelligent frameworks for industry applications, his research reflects both precision and creativity. Passionate about turning raw data into refined intelligence, Prof. Xu continues to illuminate pathways where technology, theory, and transformation intersect. 🧠💾✨

🏅 Awards and Honors

Prof. Xu Chun’s brilliance has been widely acknowledged through numerous accolades 🏆. A recipient of the esteemed “Tianshan Talent” award in the Xinjiang Uygur Autonomous Region 🌟, he has been recognized for both his intellectual depth and his regional impact. He has also earned the Third Prize in the National College Young Teachers Teaching Competition 🥉, and Second Prizes in the 9th and 12th Xinjiang Natural Science Outstanding Academic Papers 🥈—a testament to his scholarly excellence and research clarity. These honors underscore his rare ability to fuse research with education, thought with action, and theory with real-world benefit 📜💡. His achievements are more than accolades—they are milestones that reflect a lifelong devotion to discovery, teaching, and the betterment of society through scientific insight. Xu stands as an emblem of academic honor and progressive innovation in China’s research landscape. 🇨🇳🌐

🧩 Conclusion

Prof. Dr. Xu Chun stands at the confluence of intellect, innovation, and influence 🧠🌟. With a strong academic foundation, a wealth of professional experience, and a laser focus on future-forward research, he epitomizes the modern scientific leader. His ability to bridge data science theory with real-world application not only inspires his peers but also empowers the next generation of thinkers and doers 📚🤝. The impact of his work ripples across academic communities and technological frontiers alike, establishing him as an ideal candidate for the Best Researcher Award 🏅. Through his awards, projects, and publications, he has created a legacy grounded in excellence and guided by vision. As a champion of knowledge and a cultivator of potential, Prof. Xu Chun’s contributions transcend boundaries—making him not only a researcher of the present but a pioneer for tomorrow’s scientific world 🌍🚀.

Publications Top Notes

 

Shijie Zhao | Applied Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Shijie Zhao | Applied Mathematics | Best Researcher Award

Associate Professor at Liaoning Technical University, China

Assoc. Prof. Dr. Shijie Zhao is a distinguished researcher and academic at the Institute of Intelligence Science and Optimization, Liaoning Technical University, China. With a Ph.D. in Optimization and Management Decisions, his expertise lies in metaheuristic optimization, multi-objective optimization, and underwater navigation and positioning. He has made significant contributions through innovative algorithm designs and novel mathematical models, particularly in high-dimensional feature selection and robust navigation techniques. Dr. Zhao has published 9 SCI-indexed journal articles and participated in over 10 nationally and provincially funded research projects. He serves as a reviewer for leading journals including those by Elsevier, Springer, and IEEE, and holds memberships in 13 professional bodies. With strong programming skills, rigorous analytical thinking, and a commitment to scientific innovation, Dr. Zhao has also earned four research awards. His work bridges theoretical mathematics and practical applications, making him a valuable contributor to the global research community in intelligent systems and optimization.

Professional Profile 

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ORCID Profile

Education

Assoc. Prof. Dr. Shijie Zhao has a robust academic foundation anchored at Liaoning Technical University, China. He earned his B.S. degree in Science of Information & Computation in 2012, followed by a successive postgraduate and doctoral program in Mathematics and Applied Mathematics from 2012 to 2014. He went on to complete his Ph.D. in Optimization and Management Decisions in 2018. His educational trajectory highlights a deep commitment to the field of mathematical optimization and intelligent systems. Dr. Zhao’s academic excellence is also reflected in his ability to integrate theoretical knowledge with practical problem-solving, laying a strong foundation for his future research. His interdisciplinary approach blends pure mathematics with applied optimization techniques, making him uniquely positioned to contribute to emerging challenges in computational intelligence, machine learning, and navigation systems. His comprehensive training has equipped him with skills in advanced mathematical modeling, algorithm design, and statistical analysis—all crucial for his research trajectory.

Professional Experience

Dr. Shijie Zhao began his professional journey as a faculty member at Liaoning Technical University, where he is now serving as an Associate Professor and Director of the Institute of Intelligence Science and Optimization. Since 2012, he has progressed through a series of academic roles, including a postdoctoral tenure beginning in 2020. He has successfully led and participated in a range of scientific research projects sponsored by institutions such as the China Postdoctoral Science Foundation and the Department of Science & Technology of Liaoning Province. In addition to his teaching responsibilities, he has been actively involved in administrative, academic, and research leadership roles. Dr. Zhao has served as a reviewer for numerous high-impact international journals and conferences and has editorial roles in reputed scientific publications. His contributions to collaborative and interdisciplinary projects underscore his ability to bridge research and real-world applications, enhancing his standing as a key contributor in intelligent systems research.

Research Interest

Assoc. Prof. Dr. Shijie Zhao’s research interests lie at the intersection of intelligent optimization, computational mathematics, and advanced data analytics. He specializes in the development and enhancement of metaheuristic and multi-objective optimization algorithms, addressing both theoretical and application-driven challenges. His work has pioneered novel strategies for high-dimensional feature selection and optimization in machine learning contexts. Another key area of his focus is underwater navigation and positioning, where he has introduced innovative models for enhancing gravity navigation accuracy. With a strong foundation in mathematics, Dr. Zhao combines theoretical rigor with practical applicability, ensuring that his research contributes both to academic knowledge and technological development. His recent work explores how optimization strategies can be integrated into real-time systems, with implications in robotics, autonomous navigation, and engineering design. By addressing complex computational problems, Dr. Zhao’s research plays a vital role in driving forward the capabilities of intelligent systems and adaptive algorithms.

Award and Honor

Dr. Shijie Zhao has earned multiple accolades in recognition of his impactful contributions to scientific research and innovation. He has received four prestigious research awards for his work in intelligent systems, mathematical optimization, and applied computational modeling. His leadership in various national and provincial research initiatives has further cemented his reputation as a top-tier researcher in his domain. In addition to these honors, he has held editorial and reviewer positions for over ten internationally recognized journals, including publications by IEEE, Springer, and Elsevier—an acknowledgment of his expertise and academic integrity. Dr. Zhao is also an active member of 13 professional bodies, reflecting his global engagement and scholarly influence. His participation in high-impact collaborative projects and his growing citation index underscore the recognition and respect he commands in the research community. These honors validate his innovative spirit and unwavering dedication to advancing knowledge in mathematics and intelligent computing.

Conclusion

In conclusion, Assoc. Prof. Dr. Shijie Zhao exemplifies excellence in mathematical research, optimization theory, and intelligent system applications. His educational background, combined with over a decade of professional experience, positions him as a thought leader in his field. Through pioneering contributions to metaheuristic algorithms, multi-objective optimization, and underwater navigation, he bridges the gap between theoretical frameworks and practical technologies. His commitment to research integrity, academic service, and innovation has earned him widespread recognition and professional accolades. As an educator, leader, and scientist, Dr. Zhao’s multifaceted contributions reflect a deep dedication to advancing scientific knowledge and solving complex global challenges. His future endeavors are poised to have even greater impacts on the fields of artificial intelligence, data-driven decision-making, and intelligent navigation. With a strong publication record, a solid foundation in mathematics, and an expanding research network, Dr. Zhao continues to be a prominent and influential figure in the global academic landscape.

Publications Top Notes

  • Title: ID2TM: A Novel Iterative Double-Cross Domain-Center Transfer-Matching Method for Underwater Gravity-Aided Navigation
    Authors: Shijie Zhao, Zhiyuan Dou, Huizhong Zhu, Wei Zheng, Yifan Shen
    Year: 2025
    Source: IEEE Internet of Things Journal

  • Title: OS-BiTP: Objective sorting-informed bidomain-information transfer prediction for dynamic multiobjective optimization
    Authors: Shijie Zhao, Tianran Zhang, Lei Zhang, Jinling Song
    Year: 2025
    Source: Swarm and Evolutionary Computation

  • Title: Mirage search optimization: Application to path planning and engineering design problems
    Authors: Jiahao He, Shijie Zhao, Jiayi Ding, Yiming Wang
    Year: 2025
    Source: Advances in Engineering Software

  • Title: Twin-population Multiple Knowledge-guided Transfer Prediction Framework for Evolutionary Dynamic Multi-Objective Optimization
    Authors: Shijie Zhao, Tianran Zhang, Miao Chen, Lei Zhang
    Year: 2025
    Source: Applied Soft Computing

  • Title: VC-TpMO: V-dominance and staged dynamic collaboration mechanism based on two-population for multi- and many-objective optimization algorithm
    Authors: Shijie Zhao, Shilin Ma, Tianran Zhang, Miao Chen
    Year: 2025
    Source: Expert Systems with Applications

  • Title: A Novel Cross-Line Adaptive Domain Matching Algorithm for Underwater Gravity Aided Navigation
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2024
    Source: IEEE Geoscience and Remote Sensing Letters

  • Title: Triangulation topology aggregation optimizer: A novel mathematics-based meta-heuristic algorithm for continuous optimization and engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Liang Cai, Ronghua Yang
    Year: 2024
    Source: Expert Systems with Applications

  • Title: Improving Matching Efficiency and Out-of-Domain Positioning Reliability of Underwater Gravity Matching Navigation Based on a Novel Domain-Center Adaptive-Transfer Matching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Transactions on Instrumentation and Measurement

  • Title: A dynamic support ratio of selected feature-based information for feature selection
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2023
    Source: Engineering Applications of Artificial Intelligence

  • Title: Sea-horse optimizer: a novel nature-inspired meta-heuristic for global optimization problems
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Mengchen Wang
    Year: 2023
    Source: Applied Intelligence

  • Title: Improving the Out-of-Domain Matching Reliability and Positioning Accuracy of Underwater Gravity Matching Navigation Based on a Novel Cyclic Boundary Semisquare-Domain Researching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Sensors Journal

  • Title: A feature selection method via relevant-redundant weight
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2022
    Source: Expert Systems with Applications

  • Title: Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Miao Chen
    Year: 2022
    Source: Engineering Applications of Artificial Intelligence

  • Title: Improving Matching Efficiency and Out-of-domain Reliability of Underwater Gravity Matching Navigation Based on a Novel Soft-margin Local Semicircular-domain Re-searching Model
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2022
    Source: Remote Sensing

  • Title: Improving Matching Accuracy of Underwater Gravity Matching Navigation Based on Iterative Optimal Annulus Point Method with a Novel Grid Topology
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Aigong Xu, Huizhong Zhu
    Year: 2021
    Source: Remote Sensing

  • Title: A Novel Quantum Entanglement‐Inspired Meta‐heuristic Framework for Solving Multimodal Optimization Problems
    Authors: Shijie Zhao
    Year: 2021
    Source: Chinese Journal of Electronics

  • Title: A Novel Modified Tree‐Seed Algorithm for High‐Dimensional Optimization Problems
    Authors: Shijie Zhao
    Year: 2020
    Source: Chinese Journal of Electronics