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Prof. Dr. Junguo Zhang | Forestry Innovations Awards | Best Researcher Award 

Prof. Dr. Junguo Zhang, Beijing Forestry University, China

Zhang Junguo is a Professor and Doctoral Supervisor in the Automation Department at the School of Technology, Beijing Forestry University.he earned his B.S. in Electrical Engineering and Automation (1996-2000) and M.S. in Automation of Electrical Power Systems (2000-2003) from the China University of Mining and Technology. He completed his Ph.D. in Forest Engineering (2006-2009) at Beijing Forestry University. Since joining the university in 2003, Professor Zhang has advanced through various academic roles, becoming a full professor in 2016. Professor Zhang’s research focuses on intelligent forestry monitoring and information processing, with interests in automatic monitoring and identification of wild animals, Internet of Things (IoT) applications in forestry, unmanned aerial vehicles, and forestry-specialized robotics. He has contributed significantly to teaching, offering undergraduate courses such as Automated Detection Technology and Electrical Measurement Technology, and postgraduate courses like IoT Technology and Modern Sensor and Detection Technology.

Professional Profile:

SCOPUS

Summary of Suitability for the Best Researcher Award

Zhang Junguo, a professor and doctoral supervisor at the Automation Department of Beijing Forestry University, demonstrates outstanding qualifications for the Research for Best Researcher Award at Beijing Forestry University. His robust academic and professional background, impactful research contributions, and extensive academic service establish him as a strong candidate.

🎓 Education Background

  • 1996-2000: B.S. in Electrical Engineering and Automation, China University of Mining and Technology, Xuzhou, China.
  • 2000-2003: M.S. in Automation of Electrical Power System, China University of Mining and Technology, Xuzhou, China.
  • 2006-2009: Ph.D. in Forest Engineering, Beijing Forestry University, Beijing, China.

💼 Working Experience

  • 2003-2007: Assistant, Automation Department, School of Technology, Beijing Forestry University.
  • 2008-2010: Lecturer and Director of Staff Room, Automation Department, Beijing Forestry University.
  • 2011-2015: Associate Professor, Director of Staff Room, and Faculty Director, Automation Department, Beijing Forestry University.
  • 2016-Present: Professor and Doctoral Supervisor, Automation Department, School of Technology, Beijing Forestry University.
  • 2011-2012: Visiting Scholar at Forest Products Laboratory, U.S. Department of Agriculture.

🌟 Academic and Professional Achievements

  • Research Areas:
    • Intelligent forestry monitoring and information processing.
    • Automatic monitoring and identification of wild animals.
    • Internet of Things (IoT) applications in forestry.
    • Unmanned aerial vehicles (UAVs) and forestry-specific robots.
  • Teaching Contributions:
    • Undergraduate Courses: Automated detection technology and devices, Electrical measurement technology.
    • Postgraduate Courses: IoT technology and its applications, Modern sensor and detection technology.
  • Leadership and Mentorship:
    • Undergraduate teaching supervision at Beijing Forestry University.
    • Instructor for the Student Science and Technology Society.
    • Mentor for the “Liang Xi Cup” college student competition.

🏆 Awards and Honors

  • Academic Appointments:
    • Member of the Education Committee, China Association of Automation.
    • Director, Forestry Computer Application Branch, Chinese Society of Forestry.
    • Executive Director, Forest Engineering Branch, Chinese Society of Forestry.
    • Standing Committee Member, Youth Work Committee, Chinese Society of Forestry.
    • Member, Teaching Committee of Electrical Engineering and Automation, China Machinery Industry Education Association.
    • Member, Steering Committee of the Student Branch, Chinese Computer Society.

Publication Top Notes:

DeLoCo: Decoupled location context-guided framework for wildlife species classification using camera trap images

ChatDiff: A ChatGPT-based diffusion model for long-tailed classification

MDF-Net: A multi-view dual-attention fusion network for efficient bird sound classification

Multi-agent event triggered hierarchical security reinforcement learning

Adaptive image processing embedding to make the ecological tasks of deep learning more robust on camera traps images

Rare bird recognition method in Beijing based on TC-YOLO model

Prof. Dr. Junguo Zhang | Forestry Innovations Awards | Best Researcher Award

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