Dr. Xinglong Wu | Mathematics | Best Research Article Award

professor at Guangdong university of foreign studies | China

Prof. Xinglong Wu is a distinguished scholar in applied mathematics, currently serving at the School of Mathematics and Statistics, Guangdong University of Foreign Studies. His career reflects a commitment to excellence in the theoretical and applied study of partial differential equations, fluid mechanics, and nonlinear evolution equations. Over the years, Prof. Wu has authored numerous influential works in leading international journals, gaining wide recognition in the academic community. His professional journey is marked by impactful research, active collaboration, and leadership roles in academic peer review, making him a respected figure in mathematical sciences.

Profile:

Scopus | Orcid

Education:

Prof. Xinglong Wu earned his Ph.D. in Applied Mathematics from Sun Yat-sen University, specializing in advanced topics within mathematical analysis and nonlinear dynamics. Following his doctorate, he pursued postdoctoral research at the Institute of Applied Physics and Computational Mathematics under the mentorship of leading academicians. This academic foundation equipped him with a deep understanding of complex systems and advanced mathematical modeling. His educational journey reflects a blend of rigorous formal training, innovative problem-solving approaches, and exposure to interdisciplinary research environments, enabling him to bridge theoretical concepts with applied challenges in mathematical sciences.

Experience:

Prof. Xinglong Wu’s academic career spans appointments at renowned institutions, including the Chinese Academy of Sciences’ Wuhan Institute of Physics and Mathematics and Wuhan University of Technology’s Mathematical Sciences Research Center. His contributions extend beyond teaching, encompassing leadership in research projects and active participation in international academic discourse. Currently a professor and doctoral advisor, he serves as a reviewer for international journals, a national science fund review expert, and a participant in national and provincial research initiatives. His expertise is regularly sought for keynote addresses and specialized presentations at major academic conferences.

Research Interest:

Prof. Xinglong Wu research focuses on the theoretical and applied analysis of nonlinear partial differential equations, fluid mechanics, and nonlinear wave phenomena. He has made significant advances in understanding the Cauchy problem, blow-up phenomena, persistence properties, and well-posedness in complex dynamical systems. His studies often merge rigorous mathematical proofs with computational modeling, bridging theory and application. Current interests include compressible Euler equations, Degasperis–Procesi type equations, and multi-component shallow water models. These research directions have implications for mathematical physics, engineering applications, and the deeper understanding of nonlinear systems in natural sciences.

Award and Honors:

Prof. Xinglong Wu has been recognized with multiple honors for his academic and teaching excellence, including prestigious university-level teaching awards. His role as a mentor has enabled students to win top national scholarships and accolades for outstanding theses, reflecting his dedication to nurturing the next generation of scholars. His selection as a featured postdoctoral researcher and invitations to speak at major mathematical conferences underscore his professional standing. These distinctions reflect his dual commitment to advancing mathematical research and maintaining high standards in education, both in classroom teaching and in mentoring postgraduate researchers.

Publications:

Title: On the Cauchy problem for the periodic generalized Degasperis–Procesi equation
Citation: 123
year of Publications: 2011

Title: Well-posedness and global existence for the Novikov equation
Citation: 98
year of Publications: 2012

Title: Persistence properties for the modified two-component Camassa–Holm equation
Citation: 87
year of Publications: 2013

Title: Wave breaking in nonlinear shallow water wave equations, Nonlinear Anal. TMA
Citation: 76
year of Publications: 2015

Title: Blow-up phenomena for full compressible Euler equations, Nonlinearity
Citation: 92
year of Publications: 2016

Title: Qualitative analysis for generalized Zakharov equations
Citation: 65
year of Publications: 2021

Title: Finite time singularities for Degasperis–Procesi equations
Citation: 72
year of Publications: 2018

Conclusion:

Prof. Xinglong Wu’s academic career exemplifies a rare combination of research depth, teaching excellence, and service to the scientific community. His work addresses complex mathematical problems with both theoretical rigor and practical significance. By consistently publishing in high-impact journals, mentoring accomplished students, and actively contributing to global academic discourse, he has built a legacy that influences contemporary mathematical research. His dedication to the field ensures that his contributions will continue to inspire, inform, and shape advancements in applied mathematics, fostering collaboration and innovation within both academic and applied research communities.

Dr. Maedeh GholamAzad | Mathematics | Best Researcher Award

Postdoctoral Researcher at University of Kurdistan, Iran

Dr. Maedeh Gholam Azad is a distinguished postdoctoral researcher at the University of Kurdistan, specializing in optimization model design with a focus on operations research and data envelopment analysis (DEA). With a strong foundation in artificial intelligence (AI), she has contributed significantly to various domains, including supply chain management, healthcare, and environmental sustainability. Her research aims to develop intelligent methodologies that integrate AI with optimization techniques to improve decision-making and efficiency in complex systems. Passionate about innovation, she continuously explores new approaches to tackling contemporary challenges through data-driven solutions.

Profile

Scopus

Education

Dr. Gholam Azad earned her doctorate in operations research, where she concentrated on data envelopment analysis and mathematical modeling to enhance industrial and environmental efficiencies. Her academic journey provided her with extensive knowledge in AI applications for optimization and sustainable decision-making. Throughout her studies, she actively engaged in interdisciplinary research, bridging the gap between computational intelligence and real-world problem-solving. Her commitment to academic excellence and research rigor has established her as a respected scholar in her field.

Experience

With extensive experience in research and academia, Dr. Gholam Azad has undertaken multiple projects that integrate AI with optimization techniques. She has worked on evaluating the environmental impact of industrial production using DEA networks, optimizing supplier selection in the petrochemical industry through hybrid AI approaches, and applying machine learning to healthcare analytics. Beyond academia, she has collaborated with industry partners, including the petrochemical sector and educational institutions, to implement data-driven decision-support systems. Her editorial role at REA Publications further highlights her contributions to advancing research dissemination in AI and optimization.

Research Interests

Dr. Gholam Azad’s research interests lie at the intersection of AI and sustainable supply chain management, healthcare optimization, logistics, and transportation. She focuses on designing mathematical models that enhance efficiency and sustainability in various industries. Her expertise in machine learning, big data analytics, and stochastic modeling enables her to develop intelligent frameworks that address real-world challenges. She is particularly interested in leveraging AI for predictive analytics, scalable optimization, and automated decision-making in industrial applications.

Awards

Dr. Gholam Azad has been recognized for her contributions to research and innovation in AI-driven optimization. Her work has received accolades from academic societies and industry partners, particularly for her advancements in sustainable supply chain management. She has been an active member of professional organizations such as the Iranian Operations Research Society and the Iranian Data Envelopment Analysis Society, which further validates her influence in the field.

Publications

“Proposing a new integrated MEREC-NDEA algorithm for assessing and selecting the optimal sustainable suppliers: A case study,” International Transactions in Operational Research, 2024.

“Performance evaluation of rapeseed producers in Iran using the W-DEA technique,” Quarterly Journal of Agricultural Economics and Development, 2024.

“Assessing the effect of industrial products on air pollution in Iran: A novel NDEA approach considering undesirable outputs,” Environment, Development and Sustainability, 2024.

“Determination of disease risk factors using binary data envelopment analysis and logistic regression analysis, case study: a stroke risk factors,” Journal of Modelling in Management, 2023.

“Predicting Stroke Risk Based on Clinical Symptoms Using the Logistic Regression Method,” International Journal of Industrial Mathematics, 2022.

“Data envelopment analysis using binary data,” Journal of Modelling in Management, 2021.

“Hybrid method of logistic regression and DEA (Case study: Stroke),” Iranian Journal of Operation Research, 2021.

Conclusion

Dr. Maedeh Gholam Azad’s extensive expertise in AI-driven optimization and data envelopment analysis has positioned her as a leading researcher in her field. Her contributions to sustainable supply chain management, healthcare analytics, and industrial efficiency have been widely recognized. Through her interdisciplinary research, she has successfully integrated mathematical modeling with AI methodologies to develop innovative solutions for complex challenges. As a dedicated scholar and researcher, she continues to push the boundaries of optimization and artificial intelligence to foster sustainability and operational excellence in diverse industries.

Xinglong Wu | Mathematics | Best Research Article Award