Baoquan Ning | Mathematics | Best Researcher Award

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Prof. Dr. Baoquan Ning | Mathematics | Best Researcher Award

Dean of the School of Mathematics and Statistics | Liupanshui Normal University | China

Prof. Dr. Baoquan Ning is a distinguished mathematician and academic leader, currently serving as Professor and Dean of the School of Mathematics and Statistics at Liupanshui Normal University, China. He has built a strong reputation in the field of uncertainty decision-making, multi-attribute group decision-making, and fuzzy systems. Over the years, he has authored more than seventy academic papers in influential international journals and holds numerous patents as a first inventor. His career reflects both academic excellence and leadership, combining innovative research, practical applications, and educational development within China and beyond.

Publication Profile

Scopus

ORCID

Education Background

Prof. Dr. Baoquan Ning completed his Bachelor of Science in Mathematics and Applied Mathematics at Harbin Normal University, laying a solid foundation in mathematical sciences. He pursued further specialization in Applied Mathematics with a Master of Science degree from Kunming University of Science and Technology, strengthening his focus on applied research. Later, he advanced to doctoral studies in Mathematics at Sichuan Normal University, where he deepened his expertise in complex system evaluation and fuzzy decision-making. His academic journey demonstrates a steady progression of knowledge, practical application, and scholarly growth that underpins his research and teaching career.

Professional Experience

Prof. Dr. Baoquan Ning has been a dedicated faculty member at Liupanshui Normal University since the beginning of his career, gradually advancing to his current role as Dean of the School of Mathematics and Statistics. His professional contributions extend to leading and participating in numerous research projects at national and provincial levels. He has supervised English-language publications and encouraged international academic collaborations. Alongside his academic duties, he has established himself as a prolific inventor with more than seventy patents authorized under his name. His career highlights a commitment to both research innovation and educational leadership.

Awards and Honors

Throughout his academic career, Prof. Dr. Baoquan Ning has received multiple honors for his contributions to education and research. He has been recognized as a high-level innovative talent in Guizhou Province and has been named an academic leader of Liupanshui Normal University. His service and leadership have earned him honors such as “Outstanding Teacher” and “Excellent Communist Party Member.” Beyond personal achievements, his leadership roles as Executive Director of the Guizhou Mathematical Society and Council Member of the Guizhou Applied Statistics Society reflect his significant standing in the academic community and regional development.

Research Focus

Prof. Dr. Baoquan Ning’s research interests focus on uncertain and fuzzy decision-making, multi-attribute group decision-making, complex system evaluation, and educational measurement. His work addresses both theoretical advancements and real-world applications, including platform selection, system analysis, and group decision-making models. By publishing in high-impact journals, he has contributed to the advancement of fuzzy set theory, intelligent algorithms, and applied decision-making systems. His patents and research projects highlight his ability to bridge theory with practical application, making his contributions highly valuable to mathematics, computer science, and cross-disciplinary fields in modern decision sciences.

Publications Top Notes

  • Multiple attribute group decision-making using p, q-quasirung orthopair fuzzy credibility sets: Application to data literacy evaluation of scientific researchers
    Published Year: 2025
    Citation: 1

  • Some Novel Correlation Coefficients of Probabilistic Dual Hesitant Fuzzy Sets and their Application to Multi-Attribute Decision-Making
    Published Year: 2024
    Citation: 4

  • Site Selection of Wind Farms Based on Novel Probabilistic Dual Hesitant Fuzzy ExpTODIM and LogTODIM Methods
    Published Year: 2024
    Citation: 1

  • Probabilistic dual hesitant fuzzy MAGDM method based on generalized extended power average operator and its application to online teaching platform supplier selection
    Published Year: 2023
    Citation: 14

  • The cross-border e-commerce platform selection based on the probabilistic dual hesitant fuzzy generalized dice similarity measures
    Published Year: 2023
    Citation: 3

Conclusion

Prof. Dr. Baoquan Ning stands as a prominent scholar whose work has significantly advanced research in uncertainty decision-making and fuzzy systems. His prolific publication record, active participation in funded projects, and leadership within professional societies emphasize his dual role as a researcher and academic leader. Through his innovations, patents, and international collaborations, he continues to influence both theoretical research and applied methodologies. His recognition as a high-level innovative talent underscores his importance not only to Liupanshui Normal University but also to the broader development of mathematics and applied decision sciences in China.

Keying Wang | Mathematics | Best Researcher Award

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Ms. Keying Wang | Mathematics | Best Researcher Award

Ms. Keying Wang – Student, The University of Manchester, United Kingdom.

Keying Wang is a dynamic research assistant and co-author affiliated with The University of Manchester, driven by an interdisciplinary approach to tackling real-world problems in mathematics and computer science. With a growing academic presence, she has contributed to innovative projects that merge computational intelligence and engineering applications, particularly in corrosion diagnostics and energy storage. Keying is recognized for her potential to advance research in bioinspired systems and optimization algorithms. Her work reflects a commitment to practical impact through sustainable technology, especially in applying machine learning and algorithmic development for environmental and industrial challenges.

Publication Profile

Google Scholar

🎓 Education Background

Keying Wang is currently pursuing her academic journey at The University of Manchester, where she serves as a student and researcher. Her education emphasizes core principles in mathematics and computer science, equipping her with analytical and algorithmic skills crucial for innovative computational research. With a foundation in data-driven problem solving, she applies theoretical knowledge to practical research in energy systems and diagnostics. Keying’s academic background nurtures her capabilities to conduct independent studies, co-author scholarly publications, and work within interdisciplinary research teams at one of the UK’s leading institutions for scientific inquiry.

💼 Professional Experience

Keying Wang holds the role of Research Assistant and Co-Author at The University of Manchester, where she is actively engaged in conducting applied research in computational optimization and sustainable engineering solutions. Her professional experience includes contributing to a groundbreaking method for solving non-linear underdetermined equation systems for grounding grid corrosion diagnosis. Keying’s hands-on approach in developing algorithm-enhanced solutions reflects her growing expertise in computational models and real-world engineering applications. She is also contributing to novel energy storage solutions, emphasizing practical research impact even at an early stage of her academic career.

🏆 Awards and Honors

Although Keying Wang is in the early phase of her academic career, her innovative contributions and promising research potential are positioning her as a strong contender for honors such as the Best Researcher Award. Her work has been recognized within academic circles for its relevance and sustainability value, notably in energy storage research and corrosion analysis using advanced optimization techniques. She is steadily gaining visibility through scholarly publications and conference engagements, and her trajectory suggests a future marked by impactful awards and recognitions in computational sciences and green technologies.

🔬 Research Focus

Keying Wang’s research lies at the intersection of mathematics and computer science, with a strong focus on optimization algorithms, energy storage materials, and diagnostic modeling. Her notable work includes developing a novel biomass-derived hierarchical porous carbon electrode from oil palm waste, contributing to environmentally sustainable supercapacitor development. Additionally, she co-authored a paper applying an enhanced Hippopotamus Optimization Algorithm to improve corrosion diagnostics. Keying’s interests encompass algorithmic design, bioinspired computing, and sustainability-driven innovation, positioning her research to contribute meaningfully to both academic advancement and societal needs.

✅ Conclusion

In summary, Keying Wang is a motivated and innovative early-career researcher whose contributions to computational diagnostics and sustainable energy solutions are gaining scholarly attention. Her academic foundation, coupled with emerging research accomplishments, marks her as a valuable asset to the scientific community. With ongoing work rooted in practical applications and theoretical innovation, she exemplifies the qualities sought in award-winning researchers. Her efforts represent a commitment to advancing knowledge through interdisciplinary methods and responsible innovation, making her a fitting nominee for the Best Researcher Award category.

📝 Publications Top Notes

  1. A Solution Method for Non-Linear Underdetermined Equation Systems in Grounding Grid Corrosion Diagnosis Based on an Enhanced Hippopotamus Optimization Algorithm
    🔹 Published Year: 2025
    🔹 Journal: Biomimetics, Volume 10, Issue 7
    🔹 Cited by: 7 articles

  2. An Adaptive Multi-Elite Hippopotamus Algorithm for High-Dimensional Optimization and Its Wasserstein Distance Penalty Mechanism
    🔹 Published Year: 2025
    🔹 Conference: 2025 8th International Conference on Advanced Algorithms and Control Engineering (AAICE)
    🔹 Cited by: 4 articles