Assoc. Prof. Dr. Hao Zhou | Digital Image Processing | Best Researcher Award

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Hao Zhou | Digital Image Processing | Best Researcher Award

Hao Zhou, Yunnnan University, China

Dr. Hao Zhou is an Associate Professor at Yunnan University with a Ph.D. in Communication and Information Systems. With a robust background in optical engineering and postdoctoral research at Nanjing University of Science and Technology, he specializes in digital image processing, computer vision, and intelligent video surveillance. Dr. Zhou has led multiple national and provincial research projects, contributing significantly to the field through numerous publications. He is passionate about mentoring students and is currently seeking opportunities as a visiting scholar to further his collaborative research endeavors.

Professional profile :

scopus

Suitability for Best Researcher Award :

Dr. Hao Zhou has demonstrated sustained excellence in research, with a specialized focus in digital image processing, computer vision, and intelligent video surveillance—fields that are both cutting-edge and socially impactful. His academic journey, spanning a Ph.D. in Communication and Information Systems and postdoctoral work in optical engineering, showcases a deep technical foundation. His current role as an Associate Professor at Yunnan University underlines his commitment to research and education.

Education & Experience :

  • 🎓 Ph.D. in Engineering (Communication and Information Systems)
    Yunnan University, Kunming, China (2006–2011)
    Dissertation: “Research on video object detecting and tracking algorithm under complex scene.”

  • 🎓 Master’s in Engineering (Communication and Information Systems)
    Yunnan University, Kunming, China (1999–2002)
    Dissertation: “Blood cell image automatic analysis.”

  • 🎓 Bachelor of Engineering (Electrical Engineering)
    Shanghai Jiao Tong University, Shanghai, China (1990–1994)

  • 🧑‍🏫 Associate Professor & Master’s Advisor
    Yunnan University

  • 🔬 Postdoctoral Researcher in Optical Engineering
    Nanjing University of Science and Technology & China North Industries Group (2013–2016)

Professional Development :

Dr. Zhou’s career is marked by a commitment to advancing the fields of digital image processing and intelligent video surveillance. His postdoctoral research in optical engineering laid the foundation for his subsequent projects, which often intersect with cutting-edge technologies like compressive sensing and particle filter tracking. As a participant in Yunnan University’s Youth Backbone Teacher Cultivation program, he has demonstrated leadership in both research and education. His role as a master’s advisor has allowed him to mentor the next generation of engineers, fostering a collaborative and innovative academic environment.

Research Focus :

Dr. Zhou’s research primarily revolves around digital image processing, computer vision, and intelligent video surveillance. He has a keen interest in developing algorithms for object detection and tracking in complex scenes, often employing techniques like particle filters, compressive sensing, and adaptive Gaussian models. His work aims to enhance the accuracy and efficiency of surveillance systems, making significant contributions to both theoretical frameworks and practical applications in the field.

Awards & Honors :

  • 🏅 Participant, Youth Backbone Teacher Cultivation Program
    Yunnan University (2013–2016)

  • 🏅 Principal Investigator
    National Natural Science Foundation of China Project: “Key technology research of intelligent video surveillance in compulsory rehabilitation center based on behavior model analysis.”

  • 🏅 Principal Investigator
    Yunnan Provincial Department of Education Key Program: “Key technology research of target tracking under distributed cameras.”

Publication Top Notes : 

Title: Detection of Cotter Pin Defects in Transmission Lines Based on Improved YOLOv8

Citation:
P. Wang, G. Yuan, Z. Zhang, Y. Ma, H. Zhou
Electronics (Switzerland), 2025

Conclusion :

Dr. Hao Zhou’s research excellence, leadership in funded projects, commitment to mentoring, and contributions to high-impact areas like intelligent surveillance and computer vision make him a highly deserving nominee for the Best Researcher Award. His achievements reflect both depth and breadth in research, positioning him as a key contributor to the advancement of his field.

Dr. Thanh-Nghia Nguyen | Signal Processing | Best Researcher Award

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Dr. Thanh-Nghia Nguyen | Signal Processing | Best Researcher Award

Dr. Thanh-Nghia Nguyen | HCMC University of Technology and Education | Vietnam

Dr. Nguyen Thanh Nghia (PhD) is a dedicated researcher and educator in Electronics and Biomedical Engineering at Ho Chi Minh City University of Technology and Education. With expertise in Biomedical Signal Processing, Artificial Intelligence, and Electronic Engineering, his research focuses on ECG signal analysis, deep learning applications, and medical device development. Dr. Nghia has contributed extensively through publications and research projects, particularly in ECG noise elimination and heart disease classification. His work bridges the gap between AI and healthcare, advancing biomedical engineering for better patient diagnostics and monitoring. 🌍📡🧠

Professional Profile:

ORCID

Suitability for Best Researcher Award

Dr. Nguyen Thanh Nghia is a strong candidate for the Best Researcher Award due to his outstanding contributions to biomedical signal processing, artificial intelligence applications in healthcare, and electronic engineering. His research has significantly impacted medical diagnostics, ECG signal enhancement, and AI-driven healthcare solutions, making his work highly valuable in both academia and industry.

Education & Experience🎓🔬

📌 PhD in Electronics Engineering – Ho Chi Minh City University of Technology and Education (2016-2023)
📌 Master’s in Electronics Engineering – Ho Chi Minh City University of Technology and Education (2009-2012)
📌 Bachelor’s in Electrical & Electronics Engineering – Ho Chi Minh City University of Technology and Education (2002-2007)

🔧 2007-2010 – Engineer, TNHH Wonderful Sai Gon Electrics (WSE), Vietnam (Machine Maintenance, Repair & ISO Management)
📡 2010-2017 – Lecturer, Cao Thang Technical College (Electronics Engineering)
👨‍🏫 2017-Present – Lecturer & Researcher, Ho Chi Minh City University of Technology and Education (Electronics & Biomedical Engineering)

Professional Development 🚀

Dr. Nguyen Thanh Nghia continuously enhances his expertise in Biomedical Engineering and Artificial Intelligence. He has led multiple research projects, developing ECG noise filters, heart disease classification systems, and medical signal processing tools. His work integrates machine learning and deep learning models for improved healthcare applications. Dr. Nghia actively collaborates with international scholars, publishing in high-impact journals 📑. He also mentors students and professionals, shaping the future of biomedical technology. His passion for innovation in AI-driven medical devices is evident in his contributions to academia and industry, fostering advancements in diagnostic healthcare systems. 🏥💡

Research Focus 🔍📊

Dr. Nguyen Thanh Nghia’s research primarily focuses on Biomedical Signal Processing, with an emphasis on ECG signal analysis, artifact removal, and AI-driven medical diagnostics. His work in deep learning-based heart disease classification contributes to the automation of medical diagnoses and remote health monitoring 🏥📡. He also explores wearable sensor technology, EEG-based brain-computer interfaces (BCI), and AI applications in healthcare 🤖. Through his innovative research, Dr. Nghia aims to enhance health monitoring systems, reduce diagnostic errors, and advance medical signal processing techniques, ultimately improving patient care and medical technology. 📉💙

Awards & Honors 🏆🎖️

🏅 Best Research Paper Award – Recognized for outstanding contributions to Biomedical Signal Processing & AI applications 📝
🏅 Outstanding Researcher Award – Ho Chi Minh City University of Technology and Education (for excellence in AI-driven ECG analysis) 📡
🏅 Top Innovator in Medical Engineering – Honored for advancements in ECG noise elimination and AI-based medical diagnostics 🏥🧠
🏅 Young Scientist Recognition – For impactful publications in deep learning and medical signal processing 📊📚

Publication Top Notes:

    • 📌 A VGG-19 model with transfer learning and image segmentation for classification of tomato leaf disease – TH Nguyen, TN Nguyen, BV Ngo  🔗 Cited by: 69
    • 📌 A deep learning framework for heart disease classification in an IoTs-based system – TH Nguyen, TN Nguyen, TT Nguyen  🔗 Cited by: 24
    • 📌 Detection of EEG-based eye-blinks using a thresholding algorithm – DK Tran, TH Nguyen, TN Nguyen 🔗 Cited by: 17
    • 📌 Artifact elimination in ECG signal using wavelet transform – TN Nguyen, TH Nguyen, VT Ngo🔗 Cited by: 17
    • 📌 Deep Learning Framework with ECG Feature-Based Kernels for Heart Disease Classification – THN Thanh-Nghia Nguyen 🔗 Cited by: 16

 

 

Jingcheng Ke | Diffusion Models | Excellence in Research

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Jingcheng Ke | Diffusion Models | Excellence in Research

Dr. Jingcheng Ke, Osaka university, Japan.

Jingcheng Ke, Ph.D. 🎓, is a researcher at the Institute for Datability Science, Osaka University 🇯🇵. With a Ph.D. from National Tsing Hua University (NTHU) 🇹🇼, his research focuses on vision-language matching and diffusion models for image and video analysis 🖼️📹. He has worked as an AI researcher at vivo AI Lab and as an exchange student at Shenzhen Key Laboratory of Visual Object Detection and Recognition. Proficient in multiple languages 🌏 and programming 🖥️, Dr. Ke’s work bridges cutting-edge AI technologies and innovative computational methods.

Publication Profile

Googlescholar

Education & Experience:

Education

  • 🎓 Ph.D. in Communications Engineering (2019–2024)
    • National Tsing Hua University, Taiwan
    • Thesis: Referring Expression Comprehension in a Graph-based Perspective and Its Generalizations
  • 🎓 M.Sc. in Computer Application (2015–2018)
    • Shaanxi Normal University, China
    • Thesis: Face recognition based on virtual faces and sparse representations
  • 🎓 B.Sc. in Network Engineering (2010–2014)
    • Southwest Minzu University, China
    • Thesis: An improved encryption algorithm based on Data Encryption Standard

Experience

  • 🧑‍🔬 Researcher (2024–Present)
    • Institute for Datability Science, Osaka University
  • 🤖 AI Researcher (2018–2019)
    • vivo AI Lab
  • 🔬 Exchange Student (2016–2018)
    • Shenzhen Key Laboratory of Visual Object Detection and Recognition

Suitability for the Award

Dr. Jingcheng Ke is an exceptional candidate for the Excellence in Research Award, demonstrating a profound impact on AI and computational sciences. His Ph.D. research at National Tsing Hua University, focused on graph-based referring expression comprehension, has advanced the fields of vision-language matching and diffusion models for image and video analysis. With professional experience at Osaka University and vivo AI Lab, Dr. Ke has effectively bridged theoretical innovation and practical application. His technical expertise in Python, PyTorch, and C++, coupled with knowledge in matrix theory, stochastic processes, and topology, underscores his interdisciplinary strength. Dr. Ke’s groundbreaking contributions position him as a leader in AI research.

Professional Development

Dr. Jingcheng Ke’s professional journey spans academia and industry, specializing in artificial intelligence 🤖 and computer vision 👁️. His Ph.D. research at NTHU explored graph-based perspectives for referring expression comprehension, advancing the intersection of vision and language technologies 🌐. With hands-on experience in AI innovation at vivo AI Lab and collaboration with top-tier research labs, he has honed his expertise in diffusion models and image/video analysis 📊. Proficient in coding languages like Python and PyTorch 🖥️, he leverages advanced mathematical concepts like matrix theory and stochastic processes to push AI boundaries 🚀.

Research Focus

Dr. Ke’s research is centered on the intersection of vision and language 🤝, with a keen focus on diffusion models for image and video analysis 🎥. His work addresses challenges in vision-language matching, exploring graph-based approaches to enhance comprehension and generalization capabilities 🔍. Passionate about advancing AI technologies, he delves into areas like sparse representation and encryption algorithms 🔒. By integrating robust coding skills in Python and PyTorch with theoretical foundations, his research contributes to groundbreaking advancements in artificial intelligence and computational methodologies 🚀.

Awards and Honors

  • 🏆 Best Paper Award – Recognized for excellence in vision-language research.
  • 🥇 Graduate Fellowship – National Tsing Hua University, Taiwan.
  • 🥉 Outstanding Thesis Award – Shaanxi Normal University, China.
  • 🎖️ Research Excellence Recognition – vivo AI Lab, 2019.
  • 🌟 Academic Merit Scholarship – Southwest Minzu University, China.

Publication Highlights

  • 📄 An improvement to linear regression classification for face recognition – 26 citations, published in International Journal of Machine Learning and Cybernetics, 2019.
  • 📘 Referring Expression Comprehension via Enhanced Cross-modal Graph Attention Networks – 12 citations, published in ACM TOMM, 2022.
  • 🖼️ Face recognition based on symmetrical virtual image and original training image – 12 citations, published in Journal of Modern Optics, 2018.
  • 📊 Sample partition and grouped sparse representation – 8 citations, published in Journal of Modern Optics, 2017.
  • 🤖 A novel grouped sparse representation for face recognition – 7 citations, published in Multimedia Tools and Applications, 2019.

Yi Huangfu | Image Processing | Best Researcher Award

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Yi Huangfu | Image Processing | Best Researcher Award

Mr. Yi Huangfu,Yunnan Agricultural University, China.

Yi Huangfu, a postgraduate student at Yunnan Agricultural University 🎓, specializes in Smart Agriculture 🌾, focusing on Point Cloud and Image Processing, and End-to-End Object Detection and Perception 📸🤖. With a strong foundation in Computer Science from Inner Mongolia University of Science and Technology 💻, he has published impactful research on panoramic image stitching and disease detection in crops 🌽🍊. Yi has also developed an APP for Huanglongbing disease detection 📱 and holds an invention patent. Skilled in programming languages, machine learning, and Linux systems, he is passionate about advancing agricultural technology through innovation.

Publication Profile

Orcid

Education and Experience

  • 🎓 2022-2025: Master in Mechanical Design and Manufacturing, Yunnan Agricultural University
  • 🎓 2017-2021: Undergraduate in Computer Science and Technology, Inner Mongolia University of Science and Technology
  • 💻 Research: Published two papers as the first author on agricultural image processing and disease detection.
  • 🛠️ Patent: Developed a Huanglongbing detection app, earning a patent and software copyright.

Suitability for the Award

Mr. Yi Huangfu stands as an exemplary candidate for the Best Researcher Award, combining academic excellence with impactful contributions to Smart Agriculture. As a first author of groundbreaking research on crop disease detection and panoramic image processing, Yi has advanced precision farming practices. His patented innovations, including an app for Huanglongbing detection, highlight his practical expertise. Proficient in deep learning and programming, with accolades in national competitions, Yi embodies innovation and dedication in agricultural research.

Professional Development

Yi Huangfu demonstrates proficiency in deep learning, machine learning, and image processing technologies 🤖. His expertise spans Linux system programming, Java, C/C++, PHP, Python, OpenCV, and web scraping 💻. His research bridges technology and agriculture, addressing challenges in crop disease detection 🌾 using innovative solutions like the HHS-RT-DETR model and VCHS-YOLO 🌶️. Yi’s academic and technical pursuits are complemented by his strong ability to interpret English literature 📚, enabling him to stay abreast of global advancements. His contributions aim to enhance agricultural precision and productivity through cutting-edge applications 📈.

Research Focus

Yi’s research focuses on advancing Smart Agriculture 🌾 by integrating modern technologies like Point Cloud and Image Processing 📸 and Deep Learning models 🤖. His notable projects include disease detection systems for crops such as citrus and chili 🌶️🍊 and methods for image stitching in corn ear analysis 🌽. Yi’s work emphasizes creating scalable, end-to-end detection and perception systems for improving crop management efficiency 🚜. His dedication to applying AI and machine learning in agriculture bridges the gap between technology and sustainable farming 🌍.

Awards and Honors

  • 🏆 2018: NAGC Software Engineer Certificate
  • 🏅 2019: Excellent Award in the National NetGuard Security Cup
  • 🥉 2020: National Third Prize in the China College Student Programming Competition

Publication Highlights

  • 2024: HHS-RT-DETR: A Method for the Detection of Citrus Greening Disease 🍊 | Published in Agronomy 📖 
  • 2024: Research on a Panoramic Image Stitching Method for Images of Corn Ears, Based on Video Streaming 🌽 | Published in Agronomy 📖 

Dr. V Veera Raghavulu | Image processing Awards | Best Researcher Award

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Dr. V Veera Raghavulu | Image processing Awards | Best Researcher Award

Dr. V Veera Raghavulu | Image processing Awards | Best Researcher Award

Dr. V. Veera Raghavulu, born on June 15, 1975, is an esteemed academic with over 21 years of experience in Computer Science and Engineering. His career began in the industry as a Programmer at Javapoint and a Graduate Engineer at APSPDCL before transitioning to academia. He has served as a Lecturer at Alhuda Polutechic and Priyadarshni Engineering College and has been an Assistant Professor at N.B.K.R.I.S.T since 2005. Dr. Raghavulu’s teaching contributions include courses such as FLAT, IT Workshop, and DS Lab. In addition to his teaching roles, he has been involved in student welfare as a Resident Warden and has contributed to academic events as a Paper Presentation Judge for TECHYVHA 2024. He is also a permanent member of the Institution of Engineers (India), underscoring his commitment to the professional community.

Professional Profile:

Orcid

🌟 Academic Background

Dr. V. Veera Raghavulu, born on June 15, 1975, holds an extensive academic and professional background in Computer Science and Engineering. He has dedicated over 21 years to the field, with significant roles spanning from Programmer to Associate Professor.

📚 Professional Experience

Dr. V Veera Raghavulu is an accomplished academic with extensive experience in both industry and education. He began his career as a Programmer at Javapoint (2000-2001) and then served as a Graduate Engineer at APSPDCL (2001-2002). Transitioning to academia, he worked as a Lecturer at Alhuda Polutechic (2003-2005) and Priyadarshni Engineering College (2006-2008). Since 2009, he has been a dedicated Assistant Professor at N.B.K.R.I.S.T, following an earlier role as a Lecturer there (2005-2006). Dr. Raghavulu’s career spans over two decades, reflecting his commitment to education and technical expertise.

🏫 Teaching Contributions

In the academic year 2023-24, Dr. Raghavulu taught various subjects including FLAT, IT Workshop, and DS Lab. His courses have been well-received, with positive feedback from students, and he continues to guide future engineers.

📈 Additional Roles and Responsibilities

Dr. Raghavulu has taken on key roles such as Resident Warden and Co-PO Calculation Incharge, showcasing his commitment to both student welfare and academic administration.

📅 Events and Engagements

He served as a Paper Presentation Judge for TECHYVHA 2024, contributing to the academic community by evaluating emerging research and innovations.

🌐 Professional Affiliations

Dr. Raghavulu is a member of the Institution of Engineers (India) with a permanent membership, reflecting his engagement with professional bodies in his field.

Publication Top Notes:

An Intelligent Moving Object Segmentation Using Hybrid IFCM-CSS Clustering Model
  • Journal: International Journal of Pattern Recognition and Artificial Intelligence
  • Publication Year: 2024