Daoyun Xu | Algorithm Design | Best Researcher Award

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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. 📚🔬

 

Publication Profile

Scopus

Academic and Professional Background 👨‍🏫

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. 📚🔍

 

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. 🧑‍💻📊

 

Publication Top Notes 📚

  • “Generate universal adversarial perturbations by shortest-distance soft maximum direction attack” (2025) – Cited by 0 📚
  • “On the upper bounds of (1,0)-super solutions for the regular balanced random (k,2s)-SAT problem” (2024) – Cited by 0 🔍
  • “Exact satisfiability and phase transition analysis of the regular (k, d)-CNF formula” (2024) – Cited by 0 📐
  • “The Transition Phenomenon of (1,0)-d-Regular (k, s)-SAT” (2022) – Cited by 0 🔄
  • “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 🔑
  • “The phase transition analysis for the random regular exact 2-(D, k)-sat problem” (2021) – Cited by 0 🔄
  • “A compact AAA-compatible multispectral solar simulator based on spherical cap chamber” (2021) – Cited by 11 ☀️

K ASHWINI | Computer Science | Best Researcher Award

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K ASHWINI | Computer Science | Best Researcher Award

K ASHWINI, National Institute of Technology Rourkela, India

K. Ashwini is a dedicated Ph.D. candidate in Computer Science and Engineering at NIT Rourkela, specializing in deep learning applications for grading diabetic retinopathy. She holds an M.Tech. from VSSUT Burla and a B.Tech. from Synergy Institute of Engineering & Technology, Dhenkanal. Her research includes notable publications, such as her work on CNN-based diabetic retinopathy grading in Biomedical Signal Processing and Control. Skilled in Python, MATLAB, and LaTeX, she has actively participated in workshops on machine learning and signal processing. Ashwini is fluent in Hindi, Telugu, and English.

Publication profile

google scholar

Academic Background

Ms. K. Ashwini is a Research Scholar in Computer Science and Engineering (CSE) at NIT Rourkela, currently pursuing her Ph.D., with her research focused on diabetic retinopathy grading using deep learning techniques. Her advanced studies in deep learning, combined with an M.Tech. in CSE from VSSUT Burla, highlight her dedication to exploring complex topics within biomedical and computational research. She has maintained a strong academic record throughout her studies, underscoring her commitment and expertise in her field.

Research Focus and Publications

Ashwini’s primary research area is in biomedical signal processing, specifically targeting diabetic retinopathy grading using CNNs and soft attention mechanisms. She has contributed a journal article to Biomedical Signal Processing and Control and presented multiple conference papers at reputable IEEE and Springer conferences, indicating her active participation in disseminating her research findings. Notably, her publications demonstrate her capacity to employ and innovate with advanced computational methods for impactful health-related applications, a relevant focus for this award.

Technical Skills and Training

Her technical skill set, including Python, MATLAB, and LaTeX, complements her research competencies. Ashwini’s training in SQL and experience with clustering and fraud detection in mobile networks contribute to a robust and versatile research portfolio. Her academic research skills and fluency in programming languages further solidify her qualifications as a proficient researcher in her domain.

Workshops and Professional Development

Ms. Ashwini has participated in several workshops and short-term training programs across India, including those focused on biomedical signal processing, machine learning, and image processing applications. Her engagement in diverse professional development initiatives, such as faculty development programs and national seminars, showcases her continuous effort to enhance her knowledge base and technical skills.

Publication top notes

Grading diabetic retinopathy using multiresolution based CNN

Soft attention with convolutional neural network for grading diabetic retinopathy

Application of Generalized Possibilistic Fuzzy C-Means Clustering for User Profiling in Mobile Networks

Improving Diabetic Retinopathy grading using Feature Fusion for limited data samples

An intelligent ransomware attack detection and classification using dual vision transformer with Mantis Search Split Attention Network

Check for updates Modified Inception V3 Using Soft Attention for the Grading of Diabetic Retinopathy

Modified InceptionV3 Using Soft Attention for the Grading of Diabetic Retinopathy

Grading of Diabetic Retinopathy using iterative Attentional Feature Fusion (iAFF)

Conclusion

Ms. K. Ashwini exemplifies a suitable candidate for the Research for Best Researcher Award. Her specialized research in diabetic retinopathy grading, supported by a solid academic and technical background, positions her as a promising researcher. Her publications and active participation in workshops further validate her dedication and contributions to biomedical signal processing and computer vision applications, aligning well with the award’s criteria for excellence in research and innovation.