Dr. Haiyan Jiang | Team Building and Team Management | Best Researcher Award

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

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

Profile 

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Orcid 

📚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. Xin Li | Team Building and Team Management | Best Researcher Award

Dr. Xin Li, Team Building and Team Management,  Best Researcher Award

Chongqing University State Key Laboratory of Power Transmission Equipment and System Security and New Technology, China

🔗 Profile

Orcid 

Early Academic Pursuits 🎓

Xin Li’s academic journey began with a solid foundation in electrical engineering. After earning his Bachelor of Science degree in Electrical Engineering from Shandong University of Science and Technology in 2022, Xin Li pursued advanced studies at Chongqing University. Currently working towards his PhD with the College of Electrical Engineering, his early academic experiences laid the groundwork for a deep commitment to innovation and research in electrical systems. His initial studies not only demonstrated his grasp of fundamental concepts but also highlighted his passion for addressing complex issues in power transmission.

Professional Endeavors 🛠️

Xin Li’s professional journey is marked by a keen focus on the field of electrical engineering, specifically the online monitoring and fault diagnosis of electrical equipment. At Chongqing University’s State Key Laboratory of Power Transmission Equipment and System Security and New Technology, he has been actively involved in groundbreaking research that addresses critical challenges in high-voltage direct current (HVDC) transmission lines. His role involves extensive simulation and analysis, contributing significantly to the understanding and resolution of overheating issues in extra-high voltage systems.

Contributions and Research Focus 🔬

Xin Li’s research primarily addresses the lack of systematic analysis in connection fittings for extra-high voltage direct current (HVDC) transmission lines. His work has unveiled crucial insights into the causes and impacts of overheating defects. Xin Li proposed a novel model that not only analyzes problems related to ±800 kV HVDC overhead transmission lines but also extends to ultra-high voltage systems like ±500 kV. This model provides a comprehensive troubleshooting plan for defect issues, offering valuable guidance for improving fault diagnosis and maintenance strategies in power transmission.

Accolades and Recognition 🏆

Despite his relatively early career, Xin Li’s contributions have garnered recognition within the academic and professional communities. His innovative approach to HVDC transmission line issues has been acknowledged through various channels, reflecting the impact of his research. While specific accolades are not detailed, his ongoing work and the importance of his findings suggest a trajectory toward significant industry and academic recognition.

Impact and Influence 🌍

Xin Li’s research has a profound impact on the field of electrical engineering, particularly in the area of power transmission. By addressing critical gaps in the analysis and troubleshooting of HVDC transmission lines, his work enhances the reliability and safety of electrical power systems. The model he developed is expected to influence industry practices and contribute to more efficient fault diagnosis and maintenance procedures, thereby improving the overall stability and performance of power transmission networks.

Legacy and Future Contributions 🚀

Looking forward, Xin Li aims to build on his current research to explore further innovations in power transmission technology. His focus will continue to be on enhancing the reliability of HVDC systems and expanding the applicability of his models to other high-voltage contexts. By addressing unresolved issues in electrical engineering, Xin Li aspires to make enduring contributions that will shape the future of power transmission technology. His commitment to advancing the field reflects a dedication to leaving a lasting legacy of innovation and excellence.

📚 Publications

Analysis of Heating Defects in Extension Rods of Extra-High Voltage Direct Current Overhead Transmission Lines

    • Authors: Li, X.; Du, L.; Hu, Y.; Xie, H.; Luo, L.
    • Journal: Electric Power Systems Research
    • Year: 2024
Harmonic Voltage Measurement Based on Capacitive Equipment Dielectric Equivalent Model and Responding Current
    • Authors: Lin Du; Hui Feng; Xin Li; Xianjun Shao; Zhi Yang
    • Journal: Measurement Science and Technology
    • Year: 2024