Prof Dr. Yong-hai Li | Decision analysis | Best Researcher Award

Prof Dr. Yong-hai Li | Decision analysis | Best Researcher Award

Prof Dr. Yong-hai Li, Henan University of Technology, China

Prof. Dr. Yong-hai Li, a prominent professor and doctoral supervisor, holds a Ph.D. and has been a visiting scholar at the University of Windsor. His academic influence is further demonstrated through his active roles in key committees such as the Youth Working Committee of the Chinese Society for Operations Research and the Decision Science Professional Committee of the Systems Engineering Society of China. Prof. Li has led significant research projects funded by the National Natural Science Foundation of China and the Henan Province Philosophy and Social Science Planning Project. His contributions to academia have earned him recognition as a provincial young backbone teacher and social science innovation talent, underscoring his impactful role in advancing research and education in his field.

Professional Profile:

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Suitability for the Award

Prof. Dr. Yong-hai Li is highly suitable for the Best Researcher Award due to the following reasons:

  1. Significant Research Contributions: Prof. Li’s research spans multiple impactful areas including rural e-commerce, big data management, and business intelligence. His contributions have led to practical solutions and frameworks that address real-world problems, showcasing his ability to drive meaningful advancements in his field.
  2. Recognition and Awards: His impressive track record of publications, including high-impact papers and monographs, reflects his significant contributions to academia. The awards he has received underscore the quality and impact of his research.
  3. Leadership and Influence: Prof. Li’s roles as a professor, doctoral supervisor, and member of various professional committees demonstrate his leadership and influence in his field. His involvement in international academic communities and projects adds to his stature as a leading researcher.
  4. Practical Impact: The practical applications of his research, such as the development of decision-making frameworks and solutions for e-commerce challenges, highlight the real-world value of his work. This aligns well with the criteria for the Best Researcher Award, which values research that has tangible benefits and applications.

Educational and Professional Background:

Prof. Dr. Yong-hai Li holds a Ph.D. and is a professor and doctoral supervisor. His roles as a visiting scholar at the University of Windsor and a member of several key committees in the Chinese Society for Operations Research and Systems Engineering Society of China underscore his active engagement in the academic community and his influence in the field.

Academic Achievements:

Prof. Li has led and successfully completed significant research projects, including one funded by the National Natural Science Foundation of China and another supported by the Henan Province Philosophy and Social Science Planning Project. His recognition as a provincial young backbone teacher and social science innovation talent highlights his outstanding contributions to academia.

Professional Recognition and Roles:

Prof. Li is actively involved in several academic committees, including the Youth Working Committee of the Chinese Society for Operations Research and the Decision Science Professional Committee of the Systems Engineering Society of China. His involvement in these committees highlights his influential role in the academic community.

Publication Top Notes:

  • Title: Sentiment Analysis-Based Method for Matching Creative Agri-Product Scheme Demanders and Suppliers: A Case Study from China
    • Year: 2021
    • Cited by: 6
  • Title: Product Recommendation Incorporating the Consideration of Product Performance and Customer Service Factors
    • Year: 2017
    • Cited by: 8
  • Title: Generating Project Risk Response Strategies Based on CBR: A Case Study
    • Year: 2015
    • Cited by: 92
  • Title: Hybrid Similarity Measure for Case Retrieval in CBR and Its Application to Emergency Response Towards Gas Explosion
    • Year: 2014
    • Cited by: 121
  • Title: Method for Generating Emergency Alternative with Considering Implementation Effects of Emergency Alternatives
    • Year: 2014
    • Cited by: 18

 

 

Dr. Aurang Zeb | Decision-Making Awards | Excellence in Research

Dr. Aurang Zeb | Decision-Making Awards | Excellence in Research

Dr. Aurang Zeb , Central South University China, China

Aurang Zeb is a Pakistani mathematician and educator currently pursuing a PhD in Mathematics at Central South University, Changsha, Hunan, China. With over six years of teaching experience, Aurang has taught mathematics at various levels, including primary, secondary, and higher education. He holds a Master of Science in Mathematics and a Master of Philosophy in Mathematics from Abdul Wali Khan University, Mardan, Pakistan. His research focuses on fuzzy set theory, particularly in optimizing machine learning algorithms and decision-making processes. Aurang has authored several publications in high-impact journals and serves as a peer reviewer for multiple academic journals. Proficient in English, Urdu, Pashto, and currently learning Chinese, he continues to expand his expertise in mathematical sciences and their applications

Professional Profile:

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Suitability for Excellence in Research

Dr. Aurang Zeb exhibits a strong academic background and a progressive professional trajectory that qualifies him for the Excellence in Research award. His work in the application of fuzzy set theory and decision-making in various fields, coupled with his consistent educational advancements, highlight his commitment and contributions to the research community.

🎓Education:

Aurang Zeb has a robust academic background in mathematics and education. He is currently pursuing a PhD in Mathematics at Central South University, Changsha, Hunan, China, which he began in 2021. Prior to this, he completed a Master of Philosophy (M.Phil) in Mathematics from Abdul Wali Khan University, Mardan, Pakistan, where he achieved a CGPA of 3.54/4.00. He also holds a Bachelor of Education (B.Ed) in Science, completed in 2016, and an Associate Degree in Education (ADE), completed in 2017, both from Alama Iqbal Open University, Islamabad, Pakistan. His foundational studies in mathematics include a Master of Science (M.Sc) in Mathematics from Government Post Graduate College Mardan, Pakistan, where he scored 901/1100, and a Bachelor of Science (B.Sc) in Mathematics and Physics from the same institution, with a score of 377/550, completed in 2012.

🏢Work Experience:

Aurang Zeb has a diverse teaching experience spanning several years, primarily focused on mathematics education. From April 2019 to October 2022, he served as a Primary School Teacher (PST) at Govt. Primary School Nawan Killi Mardan, Pakistan, where he taught various subjects to primary-level students. Prior to this role, he worked as a Mathematics Teacher at Quaid-e-Azam Public School, Pakistan, from April 2017 to April 2019, where he instructed Matric-level students in mathematics. His teaching journey began at Al-Qalam Education System, Pakistan, where he taught mathematics to different grades at the school level from April 2015 to April 2017

🏆Awards and Achievements:

Aurang Zeb distinguished himself academically by achieving first position in the Department of Mathematics at Government Post Graduate College Mardan during the annual exam of the M.Sc program for the academic year 2013-2014.

Publication Top Notes:

  1. Optimizing decision-making in electric power system selection: A generalized approach based on Hamacher aggregation operators for q-rung orthopair fuzzy soft sets
  2. Fermatean fuzzy soft aggregation operators and their application in symptomatic treatment of COVID-19 (case study of patients identification)
  3. Fermatean Cubic Fuzzy Aggregation Operators and Their Application in Multiattribute Decision-Making Problems
  4. Aggregation operators of Pythagorean fuzzy bi-polar soft sets with application in multiple attribute decision making
  5. Multiple attribute decision-making based on cubical fuzzy aggregation operators