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 ☀️

Debajyoti Dhar | Computer Science | Best Researcher Award

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Mr. Debajyoti Dhar | Computer Science | Best Researcher Award

Mr. Debajyoti Dhar, Atal Bihari Vajpayee Indian Institute of Information Technology and Management Gwalior, India

Debajyoti Dhar is an ambitious B.Tech student with a CGPA of 7.67/10, specializing in Computer Science. He has honed his skills through impactful internships, including as a Software Development Engineer at Defence Research and Development Establishment and a Full Stack Developer at Edilitics Private Limited. Debajyoti has contributed to projects like a Decentralized FPS Game with NFT Marketplace and a Ticket Management Platform, showcasing his expertise in blockchain, cloud systems, and machine learning. He has co-authored IEEE conference papers and a journal paper, demonstrating his strong research capabilities. 💻📊🔗

 

Publication Profile

Orcid

Education Background

Debajyoti Dhar is currently pursuing a Bachelor of Technology in Computer Science at the Indian Institute of Information Technology and Management Gwalior. He started his academic journey in December 2021 and is expected to graduate in July 2025. With a CGPA of 7.67/10.00, Debajyoti has demonstrated a strong academic performance, excelling in his coursework. His education has equipped him with a solid foundation in computer science, preparing him for advanced projects and research in areas such as software development, machine learning, and blockchain technology. 📚💻🚀

 

Professional Experience

Debajyoti Dhar has gained valuable experience through multiple internships, showcasing his expertise in software development. At Defence Research and Development Establishment (Dec 2022–Oct 2023), he developed a heavy gas detection model in Java and created a 2D plotter in Python for data visualization. During his time at Edilitics Private Limited (Apr–Jun 2023), he built a robust backend using FastAPI and enhanced development efficiency with CI/CD pipelines and Docker. At Mak Design Private Limited (May–Jul 2024), he created a real-time chat module with Django and ReactJS, ensuring end-to-end encryption. 💻🔧🚀

 

Achievements

Debajyoti Dhar has demonstrated exceptional skills through various achievements. As a freelance developer for Metarootz, he built a full-stack blockchain social media project using NodeJS, ExpressJS, and MongoDB for the backend, and NextJS with TailwindCSS for the frontend. He delivered a comprehensive 5-day training bootcamp on web app deployment automation with Docker, Kubernetes, and Github Actions for industry professionals. Debajyoti has also co-authored two IEEE conference papers on computer vision and deep learning and contributed to a machine learning paper in MDPI Sensors journal. Additionally, he solved 300+ DSA questions on GFG and LeetCode. 📈💻📚

 

Research Focus

Mr. Debajyoti Dhar has contributed significantly to machine learning and optimization techniques, particularly in the context of environmental prediction. His recent work, “Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale”, published in Sensors, demonstrates his expertise in applying advanced algorithms to solve agricultural and environmental challenges. The research focuses on soil organic carbon prediction using machine learning models, emphasizing scalability and efficiency. This aligns with his broader focus on data science, AI-driven predictions, and sustainable technologies to address complex real-world problems in various domains. 🌍🤖📊

 

Publication Top Notes  

  • Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale (2024) 📚