Daoyun Xu | Algorithm Design | Best Researcher Award

Prof. Daoyun Xu | Algorithm Design | Best Researcher Award

Prof. Daoyun Xu, Guizhou Universty, China

Prof. Daoyun Xu, a renowned academic leader at Guizhou University, China, holds a Ph.D. from Nanjing University and has been a professor since 2002. He is the Director of the Guizhou Key Laboratory of Intelligent Medical Imaging and Accurate Diagnosis and a senior member of the China Computer Federation (CCF). His research focuses on computability, computational complexity, algorithm design, and SAT problems. Prof. Xu has published over 120 articles in top journals such as Annals of Mathematics and Artificial Intelligence and Science China. He leads multiple national research projects and has received numerous academic honors. πŸ“šπŸ”¬

 

Publication Profile

Scopus

Academic and Professional Background πŸ‘¨β€πŸ«

Prof. Daoyun Xu earned his Ph.D. from Nanjing University, China, in 2002, and became a professor in the same year. Currently, he serves as a professor, Ph.D. supervisor, and academic leader at the College of Computer Science and Technology, Guizhou University. He is also a senior member of the China Computer Federation (CCF) and Director of the Guizhou Key Laboratory of Intelligent Medical Imaging and Accurate Diagnosis. Prof. Xu has authored over 120 research articles, with a focus on computability, computational complexity, algorithm design, and SAT problems. His work continues to contribute to advancements in these fields. πŸ“šπŸ”

 

Research and Innovations

Prof. Xu has secured substantial funding for his research, including multiple grants from the National Natural Science Foundation of China. He has led numerous high-profile projects, showcasing his leadership and research capabilities. His work is focused on solving complex computational problems, and his contributions to the fields of artificial intelligence and mathematical computation are evident in his extensive publication record.

Areas of Research

Prof. Daoyun Xu’s research interests span across several critical areas in computer science, including computability and computational complexity. He focuses on understanding the limits of what can be computed and analyzing the resources required to solve complex computational problems. His work in algorithm design and analysis aims to develop efficient algorithms for solving real-world problems. Additionally, Prof. Xu specializes in SAT (Satisfiability) problems, which are fundamental in optimization, artificial intelligence, and mathematical logic. His research contributes to advancing these fields, providing both theoretical insights and practical solutions. πŸ§‘β€πŸ’»πŸ“Š

 

Publication Top NotesΒ πŸ“š

  • “Generate universal adversarial perturbations by shortest-distance soft maximum direction attack” (2025) – Cited by 0 πŸ“š
  • “On the upper bounds of (1,0)-super solutions for the regular balanced random (k,2s)-SAT problem” (2024) – Cited by 0 πŸ”
  • “Exact satisfiability and phase transition analysis of the regular (k, d)-CNF formula” (2024) – Cited by 0 πŸ“
  • “The Transition Phenomenon of (1,0)-d-Regular (k, s)-SAT” (2022) – Cited by 0 πŸ”„
  • “Satisfiability threshold of the random regular (s, c, k)-SAT problem” (2022) – Cited by 0 🧩
  • “Phase transition of in random balance regular exact (2s, k)-SAT problem” (2022) – Cited by 0 🌐
  • “An algorithm for solving satisfiability problem based on the structural information of formulas” (2021) – Cited by 3 🧠
  • “Satisfiability Threshold of Strictly d-regular Random (3,2s)-SAT Problem for Fixed s” (2021) – Cited by 0 πŸ”‘
  • “The phase transition analysis for the random regular exact 2-(D, k)-sat problem” (2021) – Cited by 0 πŸ”„
  • “A compact AAA-compatible multispectral solar simulator based on spherical cap chamber” (2021) – Cited by 11 β˜€οΈ