Dr. Haiyan jiang ,Team Building and Team Management, Best Researcher Award

Department of Intelligent Equipment, Shandong University of Science & Technology, Tai-an, China

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📚Early Academic Pursuits 

Haiyan Jiang’s journey in the fields of intelligent detection technology, robot technology, and pattern recognition began with a strong foundation in academics. She pursued rigorous studies, acquiring a deep understanding of cutting-edge theories and technologies. Her early academic career was marked by a commitment to mastering the principles of experiment design, data collection, and analysis. This academic rigor laid the groundwork for her subsequent research and teaching endeavors.

🛠️Professional Endeavors 

As an educator and researcher, Haiyan Jiang has significantly contributed to both national and provincial scientific research projects. She has been involved in various educational and teaching research initiatives, demonstrating a strong dedication to advancing knowledge in her field. Her professional journey is characterized by leadership in editing and compiling textbooks and monographs, which serve as valuable resources for students and fellow researchers alike.

Haiyan Jiang has a wealth of experience in applying innovative thinking to solve complex problems. Her ability to design experiments and draw meaningful conclusions has been a cornerstone of her teaching and research. She has published numerous papers in high-impact journals, highlighting her expertise and contributions to the scientific community.

🔍Contributions and Research Focus 

Haiyan Jiang’s research has primarily focused on intelligent detection technology, robot technology, and pattern recognition. Her work has involved the development and application of advanced algorithms and models to solve practical problems in these areas. Some of her notable research publications include:

  1. Coal-gangue recognition via multi-branch convolutional neural network based on MFCC in noisy environment – Published in Scientific Reports, 2023, this paper explores the use of multi-branch convolutional neural networks for coal-gangue recognition in noisy environments.
  2. Adaptive multiswarm particle swarm optimization for tuning parameter optimization of three-element dynamic vibration absorber – This study, published in Mechanical Sciences, focuses on optimizing parameters using adaptive multiswarm particle swarm optimization.
  3. State Diagnosis of Elevator Control Transformer over Vibration Signal Based on MEA-BP Neural Network – Published in Shock and Vibration, 2021, this research addresses state diagnosis using MEA-BP neural networks.
  4. Rule-based expert system to assess caving output ratio in top coal caving – Featured in PLOS ONE, 2020, this paper presents a rule-based expert system for assessing caving output ratios.
  5. Feature selection based on FDA and F-score for multi-class classification – Published in Expert Systems with Applications, 2017, this study focuses on feature selection techniques for multi-class classification.
  6. An automatic decision approach to coal–rock recognition in top coal caving based on MF-Score – This research, published in Pattern Analysis & Applications, 2017, proposes an automatic decision approach for coal-rock recognition.

🏆Accolades and Recognition 

Haiyan Jiang’s dedication and achievements have not gone unnoticed. Her work has been recognized with various awards, including a notable mention for the “Best Researcher Award” for her article on the extreme obstacle-crossing performance and multi-objective optimization of tracked mobile robots. This recognition is a testament to her relentless efforts and contributions to her field.

🌍Impact and Influence 

Throughout her career, Haiyan Jiang has made a significant impact on the scientific community and the field of intelligent detection technology. Her research has advanced the understanding and application of complex algorithms and models, providing solutions to real-world problems. Her publications have been widely cited, influencing further research and development in related areas.

🌟Legacy and Future Contributions 

Looking forward, Haiyan Jiang aims to continue her in-depth exploration in robot motion control and path planning. Her future research will likely contribute to the development of more sophisticated and efficient robotic systems. She is committed to pushing the boundaries of knowledge and technology in her field, ensuring her legacy as a pioneer in intelligent detection and robotics.

Haiyan Jiang’s career is a testament to her passion for research, her innovative approach to problem-solving, and her dedication to advancing knowledge. Her contributions have left a lasting mark on her field, and her future endeavors promise to further elevate her influence and impact.

Publications 

Coal-gangue recognition via multi-branch convolutional neural network based on MFCC in noisy environment

    • Authors: Haiyan Jiang, Dashuai Zong, Qingjun Song, ZhiJiang Liu, Jing Tian
    • Journal: Scientific Reports
    • Year: 2023

Semantic Segmentation of In-Vehicle Point Cloud With Improved RangeNet++ Loss Function

    • Authors: Jia Zhang, Haiyan Jiang, Huizhi Shao, Xiaofeng Wang, Dashuai Zong
    • Journal: IEEE Access
    • Year: 2023

Longitudinal Vibration Characteristics of Deep Sea Mining Pipe Based on ABAQUS | 基于 ABAQUS 的深海采矿扬矿管纵向振动性能

    • Authors: Qinghui Song, Linjing Xiao, Haiyan Jiang, Xun Liu, Fan Yan
    • Journal: Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University
    • Year: 2022

Adaptive multiswarm particle swarm optimization for tuning the parameter optimization of a three-element dynamic vibration absorber

    • Authors: Qinghui Song, Linjing Xiao, Qingjun Song, Haiyan Jiang, Xun Liu
    • Journal: Mechanical Sciences
    • Year: 2022

Dynamic behavior of lifting pipe with equivalent model under mining vessel heave motion

    • Authors: Qinghui Song, Haiyan Jiang, Qingjun Song, Linjing Xiao, Fan Yan
    • Journal: Journal of Mechanical Science and Technology
    • Year: 2022
Dr. Haiyan Jiang | Team Building and Team Management | Best Researcher Award

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