Dr. Jie Lv | Real-time Monitoring | Best Researcher Award

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Dr. Jie Lv | Real-time Monitoring | Best Researcher Award

Dr. Jie Lv, Kunming University of Science and Technology, China

Dr. Jie Lv is the Director of the Teaching and Research Office at Kunming University of Science and Technology, where she also serves as a Graduate Supervisor. She earned her Master’s degree in Land Resource Management and Ph.D. in Earth Exploration and Information Technology from the same institution. With a distinguished academic and research profile, Dr. Lv has led over 20 research projects—both completed and ongoing—and authored 35 peer-reviewed publications, including Tier 1 SCI and EI-indexed journals. Her work focuses on remote sensing applications for environmental monitoring, disaster assessment, and deep learning integration. A patent holder, accomplished author of three academic books, and key contributor to a nationally funded exploration project, Dr. Lv is also an active member of several professional bodies. Her dedication to interdisciplinary research and teaching excellence has significantly advanced geospatial science and remote sensing education in China.

Professional Profile:

ORCID

🏆 Summary of Suitability for Best Researcher Award

Nominee: Dr. Jie Lv
Designation: Director of Teaching and Research Office
Institution: Kunming University of Science and Technology

Dr. Jie Lv is a distinguished academic and researcher whose exceptional contributions to remote sensing, environmental monitoring, and deep learning applications position her as an ideal candidate for the Best Researcher Award. With a robust academic foundation and over a decade of experience, she has demonstrated consistent excellence in both theoretical and applied research.

🎓 Education

  • Ph.D. in Earth Exploration and Information Technology
    Kunming University of Science and Technology – 2014

  • Master’s Degree in Land Resource Management
    Kunming University of Science and Technology – 2011

💼 Work Experience

  • Director of Teaching and Research Office
    Kunming University of Science and Technology
    (Graduate Supervisor for master’s students)
    📌 Focused on remote sensing, disaster monitoring, and deep learning applications in environmental studies.

🌟 Key Achievements

  • 🧪 Research Projects: 10 completed + 11 ongoing

  • 📊 Publications: 35 peer-reviewed journal articles (19 as first/corresponding author)

    • 🥇 3 Tier 1 (SCI-indexed)

    • 🥈 7 Tier 1 (EI-indexed)

    • 🥉 5 in Tier 2 and Tier 3

  • 📚 Books Published:

    • Comprehensive Analysis and Study of Remote Sensing Survey for the Karst Mountainous Environment in Southeastern Yunnan (ISBN: 9787541682094)

    • Principles and Applications of Remote Sensing (ISBN: 978752213822)

    • Applied Research on Regional Eco-environmental Monitoring and Assessment Using Remote Sensing (ISBN: 9787568141963)

  • ⚙️ Patents: 3 granted invention patents, 6 utility model patents, 3 pending patents

  • 🛰️ Collaborative Research:
    National Science and Technology Major Project on Deep Earth Exploration (Total funding: RMB 7.05 million)

🏅 Awards & Honors

  • 🧠 CNKI Scholar – Recognized Editorial Contributor

  • 👩‍🏫 Expert Panel Member – Yunnan Land Evaluation & Registration Association

  • 🧾 Peer Reviewer – Ministry of Education Thesis Inspection System

  • 🌐 Professional Memberships:

    • Geographical Society of China (GSC)

    • China Remote Sensing Application Association (CRSAA)

    • China Association of Higher Education (CAHE)

Publication Top Notes:

Bridge Crack Segmentation Algorithm Based on Improved U-Net

Enhanced Landslide Visualization and Trace Identification Using LiDAR-Derived DEM

Prof. Dr. Weidong Jiao | Smart Detection | Best Researcher Award

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Prof. Dr. Weidong Jiao | Smart Detection | Best Researcher Award 

Prof. Dr. Weidong Jiao, Zhejiang Normal University, China

Dr. Weidong Jiao was born in Wafangdian, Liaoning, China, in 1970. He received his B.E. and M.E. degrees in Safety Engineering and Mechanical Engineering from Gansu University of Technology in 1992 and 2001, respectively, and earned his Ph.D. in Mechanical Engineering from Zhejiang University in 2004. From 2004 to 2009, he served as a Professor in the Mechanical Engineering Department at Jiaxing University. Since 2013, he has been a Professor at the School of Engineering, Zhejiang Normal University. Dr. Jiao has authored over 100 research articles and holds approximately 20 invention patents. His research focuses on smart testing and signal processing, mechanical dynamics, and condition monitoring and fault diagnosis of mechanical equipment. He also serves as an Editor for the Journal of Vibration, Measurement & Diagnosis.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award – Prof. Weidong Jiao

Prof. Weidong Jiao is a highly qualified candidate for the Best Researcher Award, based on his extensive contributions to mechanical engineering, fault diagnosis, and intelligent signal processing. His strong research background, innovative work, and leadership in academia make him a worthy contender for this prestigious recognition.

🎓 Education:

  • B.E. in Safety Engineering – Gansu University of Technology, Lanzhou (1992)
  • M.E. in Mechanical Engineering – Gansu University of Technology, Lanzhou (2001)
  • Ph.D. in Mechanical Engineering – Zhejiang University, Hangzhou (2004)

💼 Work Experience:

  • Professor, Mechanical Engineering Department, Jiaxing University (2004–2009)
  • Professor, School of Engineering, Zhejiang Normal University (Since 2013)

🏆 Achievements & Contributions:

  • 📚 Published over 100 research articles
  • 🔬 Invented approximately 20 innovations
  • 🛠️ Expertise in smart testing, signal processing, mechanical dynamics, condition monitoring, and fault diagnosis
  • 📝 Editor of Journal of Vibration, Measurement & Diagnosis

🏅 Awards & Honors:

  • 🎖️ Recognized for contributions in mechanical engineering and diagnostics
  • 🏅 Honored for advancements in fault diagnosis and condition monitoring
  • 🔍 Acknowledged for outstanding research and academic contributions in mechanical dynamics

Publication Top Notes:

Compact multiphysics coupling modeling and analysis of self-excited vibration in maglev trains

Deep learning in industrial machinery: A critical review of bearing fault classification methods

Recursive prototypical network with coordinate attention: A model for few-shot cross-condition bearing fault diagnosis

Double attention-guided tree-inspired grade decision network: A method for bearing fault diagnosis of unbalanced samples under strong noise conditions

Cross-Conditions Fault Diagnosis of Rolling Bearing Based on Transitional Domain Adversarial Network