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

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 surveillanceโ€”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 :

  • ๐ŸŽ“ Ph.D. in Engineering (Communication and Information Systems)
    Yunnan University, Kunming, China (2006โ€“2011)
    Dissertation: “Research on video object detecting and tracking algorithm under complex scene.”

  • ๐ŸŽ“ Master’s in Engineering (Communication and Information Systems)
    Yunnan University, Kunming, China (1999โ€“2002)
    Dissertation: “Blood cell image automatic analysis.”

  • ๐ŸŽ“ Bachelor of Engineering (Electrical Engineering)
    Shanghai Jiao Tong University, Shanghai, China (1990โ€“1994)

  • ๐Ÿง‘โ€๐Ÿซ Associate Professor & Master’s Advisor
    Yunnan University

  • ๐Ÿ”ฌ Postdoctoral Researcher in Optical Engineering
    Nanjing University of Science and Technology & China North Industries Group (2013โ€“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 :

  • ๐Ÿ… Participant, Youth Backbone Teacher Cultivation Program
    Yunnan University (2013โ€“2016)

  • ๐Ÿ… 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.”

  • ๐Ÿ… Principal Investigator
    Yunnan Provincial Department of Education Key Program: “Key technology research of target tracking under distributed cameras.”

Publication Top Notes :ย 

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 Zhouโ€™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.

Samsil Arefin Mozumder | Machine Vision | Best Researcher Award

Samsil Arefin Mozumder | Machine Vision | Best Researcher Award

Mr. Samsil Arefin Mozumder, China University of Mining and Technology, China.

Samsil Arefin Mozumder is a dedicated Master’s student at China University of Mining and Technology (CUMT) in Xuzhou, China, specializing in mechanical engineering, embedded machine learning, and robotics. His research focuses on IoT, machine vision, and sensor integration for industrial applications such as derailment detection and mining infrastructure anomaly detection. With a strong background in electronics and embedded systems, Samsil has contributed to multiple publications and is actively involved in projects enhancing intelligent systems for automation. He is passionate about advancing technology for real-world impactย ๐ŸŒ๐Ÿ”ง๐Ÿค–.

Publication Profile

Orcid
Googlescholar

Education & Experience:

  • China University of Mining and Technology (CUMT), 2022โ€“2025 (CGPA: 4.5/5)
    ๐ŸŽ“ย Bachelor of Science in Electrical and Electronic Engineering
  • East Delta University (EDU), Bangladesh, 2018โ€“2020 (CGPA: 3.26/4)
    ๐ŸŽ“ย Diploma in Electronics Technology
  • Chattogram Polytechnic Institute (CPI), Bangladesh, 2013โ€“2017 (CGPA: 3.12/4)
    ๐Ÿ’ผย Research Assistant
  • China University of Mining and Technology (CUMT), 2022โ€“Present
    ๐Ÿ’ผย Deputy Field Controller
  • OPSEED CO., (BD) LTD, 2020โ€“2021

Suitability for the Award

Mr. Samsil Arefin Mozumder is an excellent candidate for the Best Researcher Award, with a strong academic background and impressive research contributions in electronics, embedded machine learning, IoT, and robotics. Currently pursuing a Master’s in Mechanical Engineering at China University of Mining and Technology, he has published impactful work on intelligent systems, such as mining derailment detection and IoT-based water management. His innovative projects, including machine vision applications and autonomous robots, showcase his ability to tackle complex real-world challenges. Samsil’s interdisciplinary approach and commitment to advancing technology make him a standout researcher deserving of this prestigious recognition.

Professional Development

Samsil Arefin Mozumder’s professional development is rooted in a strong commitment to expanding his expertise in mechanical engineering, electronics, and machine learningย ๐Ÿค–. He has been involved in several cutting-edge research projects, such as derailment detection using machine vision on edge devices and smart IoT systems. His industry experience as a deputy field controller sharpened his problem-solving and project management skillsย ๐Ÿ› ๏ธ. Through his research assistantship at CUMT, he has further honed his skills in robotics, IoT, and sensor integration, contributing to publications in top conferences and journalsย ๐Ÿ“š.

Research Focus

Samsil Arefin Mozumder’s research focus is at the intersection ofย electronics, machine learning (ML), IoT, andย roboticsย ๐Ÿ”ง๐Ÿค–. He investigates embedded ML systems, edge AI, and computer vision for real-time anomaly detection and intelligent automationย ๐Ÿง . His work includes developing smart systems for mining infrastructure, including derailment detection, vertical shaft detection, and IoT-based solutions for environmental monitoringย ๐ŸŒฑ. With a passion for exploring innovative solutions in industrial automation and machine vision, Samsil aims to bridge the gap between cutting-edge technologies and practical, impactful applicationsย ๐ŸŒ๐Ÿ“ก.

Publication Highlights

  • Smart IoT-Biofloc water management system using Decision regression tree,ย 2021ย ๐Ÿ“˜๐ŸŒŠย –ย Cited by 12
  • Research on Vertical Shaft Detection System Based on CMOS-Camera and Lidar,ย IEEE Access, 2024ย ๐Ÿ“˜๐Ÿ”
  • Derailment Detection of Mining Shaft’s Rail Vehicle Using Machine Vision on Edge Device, 2024ย ๐Ÿ“…๐Ÿš‚
  • IRHA: An Intelligent RSSI based Home automation System, ย 2022ย ๐Ÿ“˜๐Ÿ