Liu Gaofeng | Mathematics | Best Researcher Award | 13449

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Dr. Liu Gaofeng | Mathematics | Best Researcher Award 

Dr. Liu Gaofeng, Leshan Normal University, China

Dr. Gaofeng Liu is a Senior Engineer and Associate Professor at the School of Mathematical Sciences, Leshan Normal University, with a concurrent position at Shaoxing Wenli University. He holds a Ph.D. in Information and Communication Engineering and specializes in machine learning applications in complex electromagnetic environments. With extensive experience in both academia and industry, including significant contributions at the 29th Research Institute of CETC, Dr. Liu has led numerous engineering projects and published widely in radar signal processing and PolSAR imaging. His current research focuses on meta-learning, integrated evaluation methods, and mathematical model knowledge bases.

Profile

Scopus

🎓 Early Academic Pursuits

Dr. Gaofeng Liu’s academic journey reflects a deep-rooted passion for mathematics and engineering, beginning in his home province of Sichuan. Born in July 1981 in Qionglai, he demonstrated an early aptitude for analytical thinking and quantitative reasoning. He pursued his undergraduate studies at Southwest Jiaotong University, earning a Bachelor’s degree in Mathematics and Applied Mathematics in 2003. Driven by a strong academic spirit, he continued his education with a Master’s degree in Applied Mathematics in 2006. Eager to explore the interface between theoretical mathematics and practical applications, Dr. Liu earned a Ph.D. in Information and Communication Engineering from the prestigious Xidian University in 2014. His doctoral studies laid a solid foundation in signal processing and machine learning, with particular emphasis on applications in complex electromagnetic environments.

🏢 Professional Endeavors

Dr. Liu began his professional career in 2006 at Neijiang Normal University, where he served as the Director of the Mathematics Laboratory. During this time, he not only contributed to academic instruction but also fostered innovation in mathematical modeling and laboratory development. From 2014 to 2022, he made a significant career transition to the 29th Research Institute of China Electronics Technology Group Corporation (CETC). In this role, he worked on advanced engineering projects, primarily focusing on signal processing, radar data analysis, and complex electromagnetic scenarios. His engineering experience honed his ability to transform real-world problems into robust mathematical frameworks, bridging the gap between theory and practice. Currently, Dr. Liu serves as Senior Engineer and Associate Professor at the School of Mathematical Sciences, Leshan Normal University, and holds a concurrent position at Shaoxing Wenli University. He also leads the Mathematics and Applied Mathematics Program and acts as the academic competition coordinator, playing a crucial role in curriculum design and talent development.

🧠 Contributions and Research Focus

Dr. Liu’s research focuses on machine learning and its application in complex electromagnetic environments, particularly in PolSAR (Polarimetric Synthetic Aperture Radar) imaging, signal decomposition, and radar signal processing. His work often involves developing efficient algorithms for data analysis and creating mathematical models for interpreting high-dimensional radar data.

He has published several influential papers in high-impact journals and conferences, such as:

  • Fast and Valid H/α Decomposition (ICARCV, 2022)

  • Nonnegative Eigenvalue Decomposition for PolSAR (Electronics Letters, 2013)

  • Yamaguchi Decomposition with Hierarchical Constraints (Journal of Electronics & Information Technology, 2013)

In addition, he holds two patents related to radar signal parameter analysis and pulse loss compensation, showcasing his ability to create practical solutions to technical challenges.

🏆 Accolades and Recognition

Though not explicitly listed, Dr. Liu’s consistent involvement in prestigious institutions and research centers reflects high professional recognition. His leadership roles—both in academia and industry—are a testament to his reliability, competence, and visionary approach. His ability to guide academic programs and research initiatives, while also serving as a bridge to engineering applications, distinguishes him as a respected figure in his field.

🌍 Impact and Influence

Dr. Liu’s work has far-reaching implications in areas such as remote sensing, national defense, and signal intelligence, where accurate radar signal interpretation is crucial. His innovations in decomposition techniques and despeckling algorithms have helped enhance the clarity and interpretability of PolSAR images, thereby advancing the capabilities of modern radar systems. As a mentor and academic leader, he plays a vital role in cultivating young minds at Leshan Normal University. His position as the academic competition coordinator underscores his dedication to nurturing innovation, critical thinking, and competitiveness among students.

🔮 Legacy and Future Contributions

Looking forward, Dr. Liu is engaged in several impactful research projects, including:

  • Meta-Learning Principles and Applications (2022–2027) – exploring AI systems that learn to learn.

  • Integrated Evaluation Methods – aimed at improving decision-making frameworks in engineering.

  • Mathematical Model Knowledge Base – building a comprehensive, reusable base of models for industrial and academic use.

These projects not only reflect emerging trends in AI and data science but also position Dr. Liu at the forefront of multidisciplinary innovation. His work is expected to contribute significantly to both academic theory and industrial practice in the years to come.

🧭 Conclusion

Dr. Gaofeng Liu embodies the rare fusion of academic excellence, engineering precision, and visionary research. From his early academic achievements in mathematics to his current work in machine learning and electromagnetic data analysis, he continues to make valuable contributions across multiple domains. His dedication to knowledge, innovation, and student mentorship ensures that his impact will resonate far beyond the confines of his institutions, shaping the next generation of scientific and engineering breakthroughs.

Yanjie Shi | Mathematics | Best Researcher Award | 13163

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Dr. Yanjie Shi | Mathematics | Best Researcher Award

Dr. Yanjie Shi, Inner Mongolia University of Technology, China

Dr. Yanjie Shi is a distinguished academic affiliated with Inner Mongolia University of Technology, China. His research focuses on sustainable energy systems, advanced materials, and innovative technologies to address energy and environmental challenges. Dr. Shi is committed to fostering technological advancements and promoting sustainable development through interdisciplinary research and collaboration.

Profile

Scopus

🌱 Early Academic Pursuits

Dr. Shi’s academic foundation was built on a strong passion for environmental science and engineering. He pursued his undergraduate studies in environmental engineering, graduating with honors. His drive for excellence led him to advanced degrees, where he specialized in waste management, renewable energy, and sustainable practices.

During his academic years, Dr. Shi focused on:

  • Understanding the impact of industrial activities on ecosystems.
  • Exploring innovative solutions to mitigate pollution.
  • Studying advanced technologies for resource recovery.

His early research laid the groundwork for his future contributions to environmental sustainability.

🏗️ Professional Endeavors

As a professor at Inner Mongolia University of Technology, Dr. Shi has held leadership roles in both teaching and research. His career is marked by:

  • Mentorship: Guiding students and young researchers in environmental studies.
  • Collaborations: Partnering with international universities, government agencies, and industries to address environmental challenges.
  • Innovation: Developing sustainable solutions to improve industrial processes and reduce environmental footprints.

Dr. Shi’s role extends beyond academia, as he actively participates in policy-making and community-driven environmental initiatives.

🔬 Contributions and Research Focus

Dr. Shi’s research interests span a wide array of topics, including:

  1. Renewable Energy: Developing technologies for harnessing wind and solar power in arid regions.
  2. Water Resource Management: Innovations in water purification and conservation for semi-arid regions like Inner Mongolia.
  3. Waste-to-Energy: Creating systems to convert industrial and agricultural waste into renewable energy.
  4. Circular Economy: Promoting practices that reduce waste and maximize resource efficiency.

Dr. Shi has published extensively in peer-reviewed journals, contributing to advancements in environmental engineering and inspiring others in the field.

🏆 Awards and Recognition

Dr. Shi’s impactful work has earned him numerous accolades, including:

  • National Green Innovation Award (2022): Recognizing his pioneering efforts in renewable energy research.
  • Excellence in Environmental Research Award (2021): Celebrating his contributions to waste management solutions.
  • Regional Sustainability Leadership Award (2020): Honoring his role in promoting sustainable practices in Inner Mongolia.

🌍 Impact and Influence

Dr. Shi’s work has had far-reaching effects, influencing:

  • Policy: Shaping environmental regulations in China and beyond.
  • Industry Practices: Encouraging sustainable practices in energy and manufacturing sectors.
  • Global Collaboration: Strengthening international research efforts on climate change and resource management.

His research has provided practical solutions to pressing environmental issues, benefitting local communities and the global scientific community.

🌟 Legacy and Future Contributions

Dr. Yanjie Shi’s legacy is built on his unwavering commitment to sustainability and innovation. Looking ahead, he aims to:

  • Expand Research: Further explore renewable energy technologies and their applications.
  • Global Impact: Foster more international collaborations to tackle global environmental challenges.
  • Inspire Future Generations: Continue mentoring young scientists and advocating for environmental awareness.

Dr. Shi’s vision is to create a sustainable future where technology and nature coexist harmoniously.

Publication Top Notes

Reliability analysis of k/n(G) degradation system under dependent competing failures

Author: Yan, Z., Shi, Y., Peng, X.

Journal: Computational and Applied Mathematic

Year: 2025

A New Single-Step Bolt Tightening Method for Multi-Bolt Flange Structures

Author: Zhong, J., Bao, J., Wang, J., … Yang, M., Shi, Y.

Journal: Buildings

Year:  2025,

 

 

 

Yu Xiao | Mathematics | Best Researcher Award

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Assoc Prof Dr. Yu Xiao | Mathematics | Best Researcher Award

Doctoral Supervisor at Harbin Institute of Technology, China.

Yu Xiao, an Associate Professor at Harbin Institute of Technology, holds a Ph.D. in Mathematics and specializes in numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. His research focuses on almost sure stability in stochastic systems under periodic intermittent control, employing advanced methodologies like stochastic analysis and multiple Lyapunov functions. Xiao has collaborated extensively with industry experts, resulting in over 40 SCI-indexed publications covering diverse topics. His contributions highlight practical applications of theoretical frameworks, reflecting his significant impact in both academic research and industrial applications.

Professional Profiles:

Education 🎓

Yu Xiao, born in 1978, completed his Ph.D. at the School of Mathematics, Harbin Institute of Technology, in 2011. He holds the position of Associate Professor at the same institution. His research focuses on numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. This background highlights his extensive academic training, current professional role, and specific research interests in mathematical methodologies applied to complex systems and control theories.

Research and Innovations

Yu Xiao is actively involved in several research areas, focusing primarily on numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. His completed and ongoing research projects include work on periodic intermittent control for almost sure stability of stochastic strict-feedback semi-Markov jump systems, indexed in SCI. He has collaborated extensively with industry experts, contributing to the publication of over 40 SCI papers. Additionally, Yu Xiao has two patents under process and has published two journal articles in prominent scientific databases. He holds membership in the Mathematical Society of Heilongjiang Province, China, demonstrating his commitment to advancing mathematical research and applications.

Contributions

In his recent research, Yu Xiao explores almost sure stability (ASS) for stochastic strict-feedback semi-Markov jump systems (SSSJSs) under periodic intermittent control (PIC). The study systematically designs virtual controllers that culminate in an actual controller, establishing ASS conditions through stochastic analysis and the application of a multiple Lyapunov function method. These conditions are intricately linked to control width and period, effectively reducing conservatism. The research substantiates its findings with compelling simulation examples, showcasing the practical applicability and robustness of the proposed methodologies in enhancing system stability and performance.

Area of Research

Yu Xiao specializes in numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. With a Ph.D. from the School of Mathematics at Harbin Institute of Technology and current role as Associate Professor at the same institution, his research spans diverse applications in control theory. His work notably explores almost sure stability in stochastic strict-feedback semi-Markov jump systems under periodic intermittent control, employing innovative methods like stochastic analysis and multiple Lyapunov functions. Xiao’s contributions extend beyond theoretical frameworks, demonstrating practical applications through extensive collaborations with industry experts and a robust publication record in SCI-indexed journals. His dedication to advancing control methodologies underscores his impact in both academic and industrial settings

Publications

  1. Almost sure synchronization of stochastic multi-links semi-Markov jump systems via aperiodically intermittent control
    • Authors: Gao, C., Gu, H., Xiao, Y., Guo, B.
    • Journal: Communications in Nonlinear Science and Numerical Simulation, 2024, 135, 108028
  2. Almost sure exponential synchronization analysis of stochastic strict-feedback systems with semi-Markov jump
    • Authors: Gao, C., Zhang, L., Zhang, H., Xiao, Y.
    • Journal: Engineering Applications of Artificial Intelligence, 2024, 133, 108453
  3. Synchronization of multi-link and multi-delayed inertial neural networks with Markov jump via aperiodically intermittent adaptive control
    • Authors: Guo, B., Xiao, Y.
    • Journal: Mathematics and Computers in Simulation, 2024, 219, pp. 435–453
  4. Dynamical analysis of higher-order rogue waves on the various backgrounds for the reverse space–time Fokas–Lenells equation
    • Authors: Song, J.-Y., Xiao, Y., Zhang, C.-P.
    • Journal: Applied Mathematics Letters, 2024, 150, 108971
  5. Aperiodically synchronization of multi-links delayed complex networks with semi-Markov jump and their numerical simulations to single-link robot arms
    • Authors: Gao, C., Guo, B., Xiao, Y., Bao, J.
    • Journal: Neurocomputing, 2024, 575, 127286
    • Citations: 2
  6. Solitonic interactions and explicit solutions for the (2+1) -dimensional nonlocal derivative nonlinear Schrödinger equation
    • Authors: Xiao, Y., Song, J.-Y., Zhang, C.-P.
    • Journal: Nonlinear Dynamics, 2024, 112(5), pp. 3797–3809
  7. Intermittent synchronization for multi-link and multi-delayed large-scale systems with semi-Markov jump and its application of Chua’s circuits
    • Authors: Guo, B., Xiao, Y.
    • Journal: Chaos, Solitons and Fractals, 2023, 174, 113762
    • Citations: 3 (Open access)
  8. Synchronization of Markov Switching Inertial Neural Networks with Mixed Delays under Aperiodically On-Off Adaptive Control
    • Authors: Guo, B., Xiao, Y.
    • Journal: Mathematics, 2023, 11(13), 2906
    • Citations: 3
  9. Soliton solutions and their dynamics of local and nonlocal (2+1)-dimensional Fokas–Lenells equations
    • Authors: Song, J.-Y., Xiao, Y., Bao, J.-C., Tang, H.-C.
    • Journal: Optik, 2023, 273, 170486
    • Citations: 1
  10. Intermittent control for synchronization of hybrid multi-weighted complex networks with reaction-diffusion effects
    • Authors: Guo, B., Xiao, Y.
    • Journal: Mathematical Methods in the Applied Sciences, 2023, 46(1), pp. 1137–1155
    • Citations: 4

 

 

Ayyub Sheikhi | Mathematics | Best Researcher Award

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Assoc Prof Dr. Ayyub Sheikhi | Mathematics | Best Researcher Award

Department of Statistics at Shahid Bahonar University of Kerman, Iran.

Ayyub Sheikhi possesses a robust set of research skills honed through years of academic and professional experience. Proficient in both theoretical and applied aspects of statistics and data science, he excels in experimental design, statistical analysis, and modeling techniques. Ayyub demonstrates proficiency in various statistical software packages, including R, and is adept at implementing advanced methodologies such as machine learning algorithms and Bayesian inference. His research skills also extend to data visualization and interpretation, allowing him to effectively communicate complex statistical findings to diverse audiences. Ayyub’s expertise in statistical research methodologies is further augmented by his ability to collaborate across interdisciplinary teams and lead projects from conception to completion. With a keen attention to detail and a commitment to methodological rigor, Ayyub Sheikhi continues to make significant contributions to the advancement of statistical science.

Professional Profiles:

Education

Ayyub Sheikhi pursued his academic journey in statistics and applied mathematics, earning his Ph.D. in Applied Mathematics from Shahid Bahonar University of Kerman, Iran, in 2012. Prior to that, he completed his Master of Science in Statistics at AmirKabir University of Technology, Tehran, Iran, and his Bachelor of Science in Statistics at Shahid Bahonar University of Kerman. His educational background equipped him with a strong foundation in mathematical and statistical principles, which he has since applied in both academic and professional settings, contributing significantly to the field of statistics and data science.

Professional Experience

Ayyub Sheikhi has garnered extensive professional experience in academia, research, and leadership roles. From 2018 to 2020, he served as the Head of the Department of Statistics at Shahid Bahonar University of Kerman, Iran, where he demonstrated his leadership skills in managing departmental affairs and fostering academic excellence. Concurrently, since 2015, he has held the position of Assistant Professor in the Department of Statistics at the same university, contributing to both teaching and research activities. In 2020, he was promoted to the position of Associate Professor, recognizing his scholarly achievements and expertise in the field. Additionally, since 2021, Ayyub has taken on the role of Head of the “Data Mining and Machine Learning” group at the Mahani Mathematical Research Institute, Shahid Bahonar University of Kerman, further showcasing his commitment to advancing statistical research and methodologies. Moreover, he has enriched his professional experience through a research fellowship at the University of Plymouth, UK, during the academic year 2023-2024, broadening his perspective and collaborating with international scholars in the field of statistics and data science.

Research Interest

Ayyub Sheikhi’s research interests encompass a diverse array of topics within the field of statistics and data science. He is particularly interested in Bayesian methods, change-point detection, and dynamic time series analysis, exploring innovative approaches to model complex data structures and uncover temporal patterns. Additionally, he focuses on copula-related techniques for analyzing dependence structures in multivariate data, aiming to develop robust methodologies for financial modeling and risk management. Ayyub also investigates machine learning methods, such as clustering algorithms and support vector machines, with a specific focus on their applications in outlier detection, classification, and regression tasks. Furthermore, he is keen on exploring the intersection of statistics with other disciplines, including economics, medicine, and engineering, to address real-world challenges and advance interdisciplinary research initiatives. Overall, Ayyub’s research interests reflect his dedication to advancing statistical theory and methodology while addressing practical problems across various domains.

Award and Honors

Ayyub Sheikhi, a prominent figure in the field of statistics and data science, has accumulated a wealth of experience and expertise over the years. He has held various academic and research positions, including serving as the Head of the Department of Statistics at Shahid Bahonar University of Kerman, Iran, from 2018 to 2020, and as an Assistant Professor and later an Associate Professor in the same department. Ayyub’s academic journey began with a Ph.D. in Applied Mathematics from Shahid Bahonar University of Kerman, Iran, in 2012, complemented by an M.Sc. in Statistics from AmirKabir University of Technology, Tehran, and a B.Sc. in Statistics from Shahid Bahonar University of Kerman. His scholarly contributions extend beyond academia, as evidenced by his involvement in various visiting appointments, publication of books, development of statistical packages, and leadership in research projects. Ayyub’s commitment to excellence and innovation in statistics continues to drive advancements in the field, positioning him as a respected authority and mentor within the academic community.

Research Skills

Dr. Sheikhi Ayyub possesses a breadth of research skills spanning statistical and mathematical domains, underpinned by a dedication to practical problem-solving. His expertise encompasses statistical inference, where he adeptly employs hypothesis testing, estimation, and model fitting to derive meaningful insights from data. Proficient in data analysis techniques, Dr. Ayyub excels in uncovering patterns and trends within complex datasets, thereby facilitating informed decision-making processes. Moreover, he demonstrates a keen understanding of machine learning algorithms, employing them for tasks ranging from classification and regression to clustering and anomaly detection, thereby enhancing predictive modeling capabilities. Additionally, Dr. Ayyub showcases proficiency in time series analysis, employing various techniques to analyze temporal data, identify patterns, and forecast future values effectively. Furthermore, his expertise extends to Bayesian statistics, copula models, and robust statistical methods, further enriching his analytical toolkit. Proficient in utilizing statistical software packages like R, Python, and MATLAB, Dr. Ayyub applies these skills across interdisciplinary research endeavors, contributing to advancements in fields ranging from healthcare and economics to engineering and finance.

Publications

  1. A two-stage Bridge estimator for regression models with endogeneity based on control function method
    • Authors: Bahador, F., Sheikhi, A., Arabpour, A.
    • Year: 2024
    • Journal: Computational Statistics
    • Volume: 39
    • Issue: 3
    • Pages: 1351–1370
    • Citations: 0
  2. Convex weak concordance measures and their constructions
    • Authors: Mesiar, R., Kolesárová, A., Sheikhi, A., Shvydka, S.
    • Year: 2024
    • Journal: Fuzzy Sets and Systems
    • Volume: 478
    • Pages: 108841
    • Citations: 1
  3. Multivariate Asymmetric Distributions of Copula Related Random Variables
    • Authors: Sheikhi, A., Arad, F., Mesiar, R.
    • Year: 2023
    • Journal: Austrian Journal of Statistics
    • Volume: 52
    • Issue: 4
    • Pages: 1–14
    • Citations: 0
  4. A dimension reduction in neural network using copula matrix
    • Authors: Sheikhi, A., Mesiar, R., Holeňa, M.
    • Year: 2023
    • Journal: International Journal of General Systems
    • Volume: 52
    • Issue: 2
    • Pages: 131–146
    • Citations: 3
  5. Convex concordance measures
    • Authors: Mesiar, R., Kolesárová, A., Sheikhi, A.
    • Year: 2022
    • Journal: Fuzzy Sets and Systems
    • Volume: 441
    • Pages: 366–377
    • Citations: 2
  6. Copula-based Berkson measurement error models
    • Authors: Ziaei, A.R., Zare, K., Sheikhi, A.
    • Year: 2022
    • Journal: Iranian Journal of Fuzzy Systems
    • Volume: 19
    • Issue: 4
    • Pages: 165–175
    • Citations: 0
  7. A heteroscedasticity diagnostic of a regression analysis with copula dependent random variables
    • Authors: Sheikhi, A., Arad, F., Mesiar, R.
    • Year: 2022
    • Journal: Brazilian Journal of Probability and Statistics
    • Volume: 36
    • Issue: 2
    • Pages: 408–419
    • Citations: 0
  8. ON ASYMMETRIC DISTRIBUTIONS OF COPULA RELATED RANDOM VARIABLES WHICH INCLUDES THE SKEW-NORMAL ONES
    • Authors: Sheikhi, A., Arad, F., Mesiar, R.
    • Year: 2022
    • Journal: Kybernetika
    • Volume: 58
    • Issue: 6
    • Pages: 984–995
    • Citations: 1
  9. Asymmetric distributions based on the t-copula
    • Authors: Arad, F., Sheikhi, A.
    • Year: 2022
    • Conference: 9th Iranian Joint Congress on Fuzzy and Intelligent Systems, CFIS 2022
    • Citations: 0
  10. On a generalization of the test of endogeneity in a two stage least squares estimation
    • Authors: Sheikhi, A., Bahador, F., Arashi, M.
    • Year: 2022
    • Journal: Journal of Applied Statistics
    • Volume: 49
    • Issue: 3
    • Pages: 709–721
    • Citations: 11

 

 

DROH ARSENE BEHI | Mathematics | Best Researcher Award

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Dr. DROH ARSENE BEHI | Mathematics | Best Researcher Award

Assistant Professor of UNIVERSITE DE MAN, COTE D’IVOIRE, Côte d’Ivoire.

Dr. Droh Arsene Behi is a distinguished mathematician with a PhD in Mathematics and Applications from Université Félix Houphouët-Boigny, specializing in EDP, Numerical Analysis, and Optimization. He holds a Master’s degree in Mathematics and Applications, a Master’s in Mathematical Sciences, a Bachelor’s degree in Mathematical Sciences, and a General University Diploma, all from Université Félix Houphouët-Boigny. Dr. Behi has a rich professional background, having worked as a secondary school teacher at the Ministry of Education in Côte d’Ivoire from 2008 to 2015 and again from 2018 to 2022. Since 2022, he has been a Lecturer-Researcher at the University of Man. Proficient in French and English, and skilled in software like Word, Excel, Geogebra, and Scilab, Dr. Behi is known for his dedication to mathematics and computing, and his ability to work under pressure both individually and in teams.

Professional Profiles:

Education

Dr. Droh Arsene Behi has an extensive academic background in mathematics, culminating in a doctoral degree. He earned his PhD in Mathematics and Applications, specializing in EDP, Numerical Analysis, and Optimization, from Université Félix Houphouët-Boigny in Côte d’Ivoire, completing his thesis on September 1, 2021. Prior to his doctorate, Dr. Behi obtained a Master of Mathematics and Applications with a focus on EDP, Numerical Analysis, and Optimization from the same university in 2014-2015. He also holds a Master’s degree in Mathematical Sciences, which he completed in 2013-2014, and a Bachelor’s degree in Mathematical Sciences, obtained in 2011-2012, both from Université Félix Houphouët-Boigny. Dr. Behi’s foundational education includes a General University Diploma in Mathematical Sciences, which he earned in 2004-2005 from Université Félix Houphouët-Boigny. His academic journey began with a Baccalaureate Series C from Lycée Moderne de Man, Côte d’Ivoire, completed in 1998-1999. Throughout his educational path, Dr. Behi has consistently focused on mathematical sciences, developing a deep expertise in numerical analysis and optimization.

Professional Experience

Dr. Droh Arsene Behi has accumulated extensive professional experience in the field of education and research. From 2008 to 2015, and again from 2018 to 2022, he served as a secondary school teacher under the Ministry of Education, Technical Education, and Vocational Training in Côte d’Ivoire. During this period, he imparted knowledge and fostered academic growth among his students. In 2022, he transitioned to higher education as a Lecturer-Researcher at the Ministry of Higher Education and Scientific Research, University of Man, Côte d’Ivoire. His role involves not only teaching but also contributing to academic research, particularly in the areas of EDP, Numerical Analysis, and Optimization. Throughout his career, Dr. Behi has demonstrated a strong commitment to education, reflected in his continuous efforts to enhance his teaching methodologies and research capabilities. His proficiency in software tools such as Word, Excel, Geogebra, and Scilab has further augmented his teaching and research efficiency.

Research Interest

Dr. Droh Arsene Behi’s research interests lie primarily in the field of nonlinear analysis, particularly focusing on EDP (partial differential equations), numerical analysis, and optimization. His work aims to advance theoretical understanding and practical applications of these mathematical concepts. He is deeply engaged in exploring innovative solutions and methodologies within these domains, contributing significantly to the body of knowledge in mathematical sciences.

Award and Honors

Throughout his academic and professional journey, Dr. Behi has received several awards and honors. Notably, he earned a Doctoral thesis in Mathematics and Applications with a specialization in EDP, Numerical Analysis, and Optimization from the Université Félix HOUPHOUËT-BOIGNY, showcasing his expertise and dedication to his field. His academic achievements and contributions to mathematics have been recognized by his peers and institutions alike, underscoring his commitment to excellence in research and education.

Research Skills

Dr. Behi possesses a robust set of research skills that have significantly contributed to his success as a researcher and educator. He is proficient in various software tools essential for mathematical analysis, including Word, Excel, Geogebra, and Scilab. His ability to conduct thorough and precise numerical analyses, combined with his expertise in optimization techniques, enables him to tackle complex mathematical problems effectively. Additionally, Dr. Behi’s strong foundation in nonlinear analysis and his practical approach to applying theoretical concepts to real-world scenarios highlight his versatility and capability as a researcher in the field of mathematics.

Publications

  1. Study of Nonlinear Second-Order Differential Inclusion Driven by a Φ-Laplacian Operator Using the Lower and Upper Solutions Method
    • Authors: Béhi, D.A., Adjé, A., Etienne Goli, K.C.
    • Journal: Journal of Mathematics, 2024, 2024, 2258546
    • Citations: 0
  2. A Variational Method for Multivalued Boundary Value Problems
    • Authors: Béhi, D.A., Adjé, A.
    • Journal: Abstract and Applied Analysis, 2020, 2020, 8463263
    • Citations: 0

 

 

Abdu Qaid Saif Alameri | Mathematics | Best Researcher Award

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Assoc Prof Dr. Abdu Qaid Saif Alameri | Mathematics | Best Researcher Award

University requirements coordinator  of University of Science and Technology, Yemen.

Dr. Abdu Qaid Saif Alameri is an accomplished academician and researcher in the field of mathematics. Holding the position of Associate Professor at the Department of Biomedical Engineering, University of Science and Technology, he is recognized for his contributions to both academia and research. Dr. Alameri obtained his Ph.D. from the University of Science and Technology, Sana’a, Yemen, graduating with distinction in 2018. Since then, he has been actively involved in teaching applied mathematics and coordinating university requirements, alongside his research pursuits. His research interests primarily revolve around graph theory and related disciplines, including theoretical computer science, fuzzy graphs, and mathematical nano-science. Dr. Alameri has made significant contributions to these areas through his publications, which include books and numerous articles published in reputable journals indexed in databases like Scopus and Web of Science. Furthermore, he serves as a reviewer and editor for several international journals, contributing to the dissemination of scholarly work and advancing the field.

 

 

Professional Profiles:

Education

Dr. Abdu Qaid Saif Alameri holds both bachelor’s and master’s degrees from Taiz University. He pursued his Ph.D. at the University of Science and Technology, Sana’a, Yemen, where he graduated in 2018 with an excellent grade. Dr. Alameri’s academic journey has been marked by a consistent dedication to excellence, leading to his current role as an Associate Professor of Mathematics at the University of Science and Technology of Yemen. His educational background has equipped him with a robust foundation in applied mathematics, graph theory, and other specialized areas within the field of mathematics.

Professional Experience

Dr. Abdu Qaid Saif Alameri has accumulated 15 years of professional experience, primarily within the academic realm. He currently serves as an Associate Professor of Mathematics in the Department of Biomedical Engineering at the University of Science and Technology. In this role, he fulfills various responsibilities, including lecturing on applied mathematics and coordinating university requirements and basic sciences. Dr. Alameri’s extensive teaching experience spans over 200 courses across diverse educational, research, and administrative domains. Additionally, he has contributed significantly to the field of mathematics through his research endeavors, publication of books and articles, and participation in scientific conferences. His expertise extends to discrete mathematics, graph theory, theoretical computer science, fuzzy graph theory, mathematical chemistry, and mathematical nanoscience. Dr. Alameri’s profound commitment to academia and research is evident in his comprehensive portfolio of scholarly achievements and contributions to the advancement of mathematical knowledge.

Research Interest

Dr. Abdu Qaid Saif Alameri’s research interests encompass various aspects of mathematics, with a focus on discrete mathematics, graph theory, theoretical computer science, fuzzy graph theory, mathematical chemistry, and mathematical nanoscience. He is particularly intrigued by the application of mathematical principles in diverse fields, including biomedical engineering. Through his research, Dr. Alameri aims to explore fundamental mathematical concepts and their practical implications, seeking innovative solutions to complex problems. His interdisciplinary approach underscores the significance of mathematical modeling and analysis in addressing real-world challenges. Additionally, Dr. Alameri is committed to advancing the frontiers of knowledge in his areas of expertise, contributing to the development of novel algorithms, mathematical frameworks, and analytical techniques. His research endeavors reflect a dedication to both theoretical exploration and practical application, with the overarching goal of fostering advancements in mathematical sciences and their interdisciplinary applications.

Award and Honors

Dr. Abdu Qaid Saif Alameri, an Associate Professor of Mathematics at the University of Science and Technology, Yemen, boasts an illustrious career marked by remarkable achievements and contributions to the field of mathematics. With a Bachelor’s and Master’s degree from Taiz University and a Ph.D. from the University of Science and Technology, Sana’a, Yemen, he graduated with distinction in 2018. Currently serving as a faculty member in the College of Engineering at the University of Science and Technology of Yemen, Dr. Alameri holds the position of lecturer in applied mathematics and also serves as the coordinator for university requirements and basic sciences. His expertise spans various domains, including graph theory, theoretical computer science, and mathematical chemistry. Additionally, he is a prolific researcher with numerous publications in esteemed international journals, earning him recognition as a multiple-time recipient of the Best Researcher Award in Engineering and Computer Science. Over his 15 years of teaching experience, Dr. Alameri has delivered more than 200 courses, showcasing his commitment to education and academic excellence.

Research Skills

Dr. Abdu Qaid Saif Alameri brings a wealth of expertise and experience to his role as an Associate Professor of Mathematics at the Department of Biomedical Engineering, University of Science and Technology. With a solid educational background, including a Ph.D. from the University of Science and Technology, Sana’a, Yemen, he graduated with honors in 2018. Since then, he has been an integral part of the academic faculty, actively contributing to both teaching and research endeavors. His academic journey encompasses a diverse range of responsibilities, including lecturing in applied mathematics, coordinating university requirements, and overseeing basic sciences. Furthermore, Dr. Alameri is a dedicated researcher, with a particular focus on graph theory and its branches, such as theoretical computer science, fuzzy graphs, and mathematical nano-science. He has demonstrated his commitment to academic excellence through numerous publications, including books and over fifty-five articles, many of which are indexed in reputable databases like Scopus and Web of Science. Dr. Alameri’s contributions extend beyond research, as he serves as a reviewer and editor for several international journals. Moreover, he has actively participated in scientific conferences, presenting his findings and fostering collaboration within the academic community. With over fifteen years of teaching experience and a track record of scholarly achievements, Dr. Abdu Qaid Saif Alameri continues to make significant contributions to the field of mathematics and its applications in various domains.

Publications

  1. Title: Y-index of some graph operations
    • Authors: A. Alameri, N. Al-Naggar, M. Al-Rumaima, M. Alsharafi
    • Journal: International Journal of Applied Engineering Research (IJAER)
    • Volume: 15
    • Issue: 2
    • Pages: 173-179
    • Year: 2020
    • Citations: 60
  2. Title: Topological indices of the mk-graph
    • Authors: A. Ayache, A. Alameri
    • Journal: Journal of the Association of Arab Universities for Basic and Applied …
    • Volume: 34
    • Year: 2017
    • Citations: 34
  3. Title: Y-coindex of graph operations and its applications of molecular descriptors
    • Authors: A. Alameri, M. Al-Rumaima, M. Almazah
    • Journal: Journal of Molecular Structure
    • Volume: 1221
    • Pages: 128754
    • Year: 2020
    • Citations: 32
  4. Title: Second hyper-zagreb index of titania nanotubes and their applications
    • Author: A. Alameri
    • Journal: IEEE access
    • Volume: 9
    • Pages: 9567-9571
    • Year: 2021
    • Citations: 28
  5. Title: Enumeration of spanning trees in a chain of diphenylene graphs
    • Authors: A. Modabish, M.N. Husin, A.Q. Alameri, H. Ahmed, M. Alaeiyan, M.R. Farahani
    • Journal: Journal of Discrete Mathematical Sciences and Cryptography
    • Volume: 25
    • Issue: 1
    • Pages: 241-251
    • Year: 2022
    • Citations: 27
  6. Title: The hyper-Zagreb index of some complement graphs
    • Authors: M. Alsharafi, M. Shubatah, A. Alameri
    • Journal: Advances in Mathematics: Scientific Journal
    • Volume: 9
    • Issue: 6
    • Pages: 3631-3642
    • Year: 2020
    • Citations: 24
  7. Title: Zagreb indices, Hyper Zagreb indices and Redefined Zagreb indices of conical graph
    • Authors: A. Alameri, M. Shubatah, M. Alsharafi
    • Journal: Advances in Mathematics: Scientific Journal
    • Volume: 9
    • Issue: 6
    • Pages: 3631-3642
    • Year: 2020
    • Citations: 23
  8. Title: On the Hyper-Zagreb coindex of some graphs
    • Authors: M.S. Alsharafi, M.M. Shubatah, A.Q. Alameri
    • Journal: J. Math. Comput. Sci.
    • Volume: 10
    • Issue: 5
    • Pages: 1875-1890
    • Year: 2020
    • Citations: 20
  9. Title: The forgotten index of complement graph operations and its applications of molecular graph
    • Authors: M.S. Alsharafi, M.M. Shubatah, A.Q. Alameri
    • Journal: Open Journal of Discrete Applied Mathematics
    • Volume: 3
    • Issue: 3
    • Pages: 53-61
    • Year: 2020
    • Citations: 17
  10. Title: The Second Hyper-Zagreb Coindex of Chemical Graphs and Some Applications
    • Authors: A. Ayache, A. Alameri, M. Alsharafi, H. Ahmed
    • Journal: Journal of Chemistry
    • Year: 2021
    • Pages: 1-8
    • Citations: 16