Yabo Wu | Computer Science | Best Researcher Award

Mr. Yabo Wu | Computer Science | Best Researcher Award

Mr. Yabo Wu, Guizhou University, China.

🎓 Mr. YaBo Wu is a Ph.D. scholar in Software Engineering at Guizhou University, focusing on computer vision, especially image enhancement and depth estimation using deep learning. 🧠 He has published in SCI Q1 and Q3 (CCF-C) journals, contributing innovative AI methods for image dehazing. 📸 His research bridges theory and application, driving AI-powered solutions for real-world systems. 🤖 A fast learner and team player, he thrives in dynamic R&D environments. 💡

🎓 Early Academic Pursuits

Mr. YaBo Wu embarked on his academic journey at Guizhou University, earning his Bachelor’s degree in Computer Science and Technology. Demonstrating early promise in technology and innovation, he continued at the same institution to pursue a Ph.D. in Software Engineering. His foundational academic background laid the groundwork for his future contributions to cutting-edge research in computer vision and artificial intelligence.

💼 Professional Endeavors

Currently immersed in doctoral research, Mr. Wu exhibits a strong commitment to bridging theoretical knowledge with real-world solutions. He excels in collaborative R&D settings, where his adaptability and technical acumen stand out. His professional demeanor is complemented by his ability to swiftly acquire new skills and integrate into multidisciplinary teams.

🔬 Contributions and Research Focus On Computer Science 

Mr. Wu’s primary research lies in computer vision, with a focus on image enhancement and depth estimation, utilizing deep learning models. He has contributed to the field through his work on single-image dehazing, which is vital for multimedia clarity and autonomous systems. His models emphasize frequency and spatial domain decoupling, enhancing feature recognition and semantic restoration.

🌍 Impact and Influence

Through his innovative contributions such as DAF-Net and DDLNet, Mr. Wu has enhanced the robustness of AI-driven solutions. His research advances not only academic knowledge but also real-world applications, especially in autonomous systems, multimedia processing, and environmental perception technologies.

🧠 Research Skills

YaBo Wu exhibits exceptional expertise in:

  • Deep learning algorithm design

  • Computer vision model optimization

  • Image dehazing and depth estimation techniques

  • Frequency and spatial domain feature analysis
    He combines technical rigor with creative problem-solving, enabling him to produce high-impact research.

🏅 Awards and Honors

Mr. Wu’s research achievements and published works in top-tier SCI journals underscore his recognition in the academic community. His ability to publish in Q1 and Q3 journals speaks to the quality and relevance of his work.

🏛️ Legacy and Future Contributions

With a passion for pushing the boundaries of AI, Mr. Wu is poised to make lasting contributions to both academic research and technological innovation. His focus on developing robust, real-time solutions for vision-based systems ensures that his work will continue influencing autonomous navigation, smart surveillance, and multimedia enhancement for years to come.

Publications Top Notes

🧪 1.  Distribution-Decouple Learning Network: An Innovative Approach for Single-Image Dehazing with Spatial and Frequency Decoupling
📘 Journal: The Visual Computer
📅 Year: March 2025
📌 Key Focus: Proposes DDLNet, decoupling haze and object features across spatial and frequency domains for superior dehazing.

🧠 2 . A Frequency-Domain Dynamic Amplitude Filtering Method for Single-Image Dehazing with Harmony Enhancement
📘 Journal: Expert Systems with Applications
📅 Year: 2025
📌 Key Focus: Introduces DAF-Net for dehazing, using amplitude components and global-local feature balancing for improved semantic recovery.

Abhilash Pati | Computer Science | Research Pioneer Award in Biomedical Sciences | 1881

Dr. Abhilash Pati | Computer Science | Research Pioneer Award in Biomedical Sciences 

Dr. Abhilash Pati, Siksha O Anusandhan University, Bhubaneswar, India

Dr. Abhilash Pati is an accomplished Assistant Professor in the Department of Computer Science and Engineering at Siksha ‘O’ Anusandhan University, Bhubaneswar, India. With over 15 years of academic and research experience, he specializes in Artificial Intelligence, Machine Learning, Blockchain, IoT, and Fog Computing. He has authored three books, published over 60 research articles indexed in Scopus and WoS, and holds three patents, including a granted design utility. His work is widely recognized in high-impact journals such as IEEE Access, Scientific Reports, and PLOS ONE. Dr. Pati is also UGC-NET qualified and actively mentors students and research initiatives.

Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Abhilash Pati’s academic journey began with a strong passion for technology and computing, which later shaped his extensive career in computer science. From his early days, he exhibited a deep curiosity in how systems work, leading him to pursue higher education in Computer Science and Engineering. His dedication and academic rigor earned him recognition early on, culminating in qualifying the prestigious UGC-NET, a testament to his proficiency and commitment to academic excellence in India. His foundational training not only built his core technical skills but also fostered an analytical mindset that would serve as the cornerstone for his research pursuits in artificial intelligence and emerging technologies.

🧑‍🏫 Professional Endeavors

Dr. Abhilash Pati currently serves as an Assistant Professor in the Department of Computer Science and Engineering at Siksha ‘O’ Anusandhan University, Bhubaneswar, India, a premier institution recognized for academic innovation and research. With over 15 years of experience, Dr. Pati has built a career marked by dedication to teaching, curriculum development, and student mentorship.

Throughout his tenure, he has engaged in the delivery of undergraduate and postgraduate courses, supervised student projects, and contributed to the design of industry-aligned academic programs. His role is not limited to classroom instruction; he is actively involved in research groups and collaborative initiatives that bridge the gap between academia and industry. This dual focus on pedagogy and innovation has made him a respected figure among students and peers alike.

🔬 Contributions and Research Focus

Dr. Pati’s research spans several cutting-edge domains, including Artificial Intelligence (AI), Machine Learning (ML), Blockchain Technology, Internet of Things (IoT), and Fog Computing. These fields represent the frontier of technological advancement, and Dr. Pati’s contributions have helped propel research in these areas, especially in applications related to smart systems and intelligent data processing.

He has authored and co-authored over 60 research publications, many of which are indexed in Scopus and Web of Science (WoS). His work is regularly published in high-impact journals such as IEEE Access, Scientific Reports (Nature Portfolio), and PLOS ONE, reflecting the global recognition of his scholarly output.

Additionally, he has authored three academic books and holds three patents, including a granted design utility patent—further illustrating the practical implications of his research and its potential for technological innovation.

🏅 Accolades and Recognition

Dr. Pati’s academic and professional excellence has not gone unnoticed. His qualification in UGC-NET speaks volumes about his academic merit. Beyond that, his prolific publication record, patent filings, and scholarly books underscore his status as a thought leader in his field. His articles are frequently cited by researchers worldwide, and he has often been invited as a reviewer and editor for reputed international journals and conferences.

Moreover, his contributions are instrumental in shaping institutional research strategies, leading to enhanced collaborations and interdisciplinary research output within his university and beyond.

🌐 Impact and Influence

Dr. Pati’s influence extends far beyond the lecture hall or laboratory. As a mentor, he has guided numerous students toward academic excellence and research competence. Many of his mentees have gone on to pursue higher education, research careers, or roles in the tech industry, thanks to the foundational skills and inspiration he provided.

His interdisciplinary approach—linking AI with Blockchain, or IoT with Fog Computing—has opened up new research directions for his peers and collaborators. Furthermore, his publications have served as reference points in academia and industry, helping shape conversations around the ethical, scalable, and efficient deployment of smart technologies.

🌟 Legacy and Future Contributions

Dr. Abhilash Pati’s journey is one of sustained growth, intellectual curiosity, and purposeful impact. Looking ahead, he is poised to continue contributing to the evolving technological landscape by focusing on sustainable computing, ethical AI, and decentralized systems. His vision includes building robust academic-industry partnerships and creating innovation hubs that foster student-led research and startups.

His legacy will not just be defined by the number of papers or patents, but by the culture of curiosity, critical thinking, and compassion that he instills in the next generation of computer scientists. Through teaching, mentorship, and research, Dr. Pati is building a future where technology serves humanity more intelligently and equitably.

Publication Top Notes

An IoT-fog-cloud integrated framework for real-time remote cardiovascular disease diagnosis

Author: A Pati, M Parhi, M Alnabhan, BK Pattanayak, AK Habboush, …
Journal: Informatics
Year: 2023

Heartfog: Fog computing enabled ensemble deep learning framework for automatic heart disease diagnosis

Author: A Pati, M Parhi, BK Pattanayak
Journal: Intelligent and Cloud Computing
Year: 2022

COVID-19 pandemic analysis and prediction using machine learning approaches in India

Author: A Pati, M Parhi, BK Pattanayak
Journal: Advances in Intelligent Computing and Communication
Year: 2023

A review on prediction of diabetes using machine learning and data mining classification techniques

Author: A Pati, M Parhi, BK Pattanayak
Journal: International Journal of Biomedical Engineering and Technology
Year: 2021