Yuanyuan Zhou | Engineering | Best Researcher Award

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Dr. Yuanyuan Zhou | Engineering | Best Researcher Award

Yuanyuan Zhou at Anhui University, China

Summary:

Yuanyuan Zhou is a dedicated researcher in the field of electronic information systems, specializing in intelligent perception, performance evaluation, and deep learning. His contributions to the field have addressed key challenges in machinery health management, such as noise reduction and data imbalance in RUL prediction models. Dr. Zhou is a Student Member of the Chinese Society of Vibration Engineering and has received multiple awards for his research, including best paper and poster awards at international conferences.

Zhou is passionate about creating intelligent and reliable solutions for industrial applications, with a vision to advance the capabilities of condition monitoring and performance analysis in rotating machinery systems.

Professional Profile:

👩‍🎓Education:

Yuanyuan Zhou received his B.S. and M.S. degrees in 2018 and 2021, respectively, from Anhui University of Science and Technology, Huainan, China. He is currently a Ph.D. student in Electronic Information at the School of Electrical Engineering and Automation, Anhui University, Hefei, China.

🏢 Professional Experience:

Zhou has over six years of experience in intelligent perception and information processing, focusing on condition monitoring and performance evaluation of machinery systems. His work emphasizes overcoming challenges such as data imbalance and noise in Remaining Useful Life (RUL) predictions for rotating machinery systems. He has contributed significantly to the development of robust intelligent models to enhance system reliability.

Research Interests:

  • Intelligent perception and information processing
  • Performance evaluation and condition monitoring
  • Deep learning applications in industrial systems

Author Metrics:

  • Publications: 6 peer-reviewed journal papers in high-impact journals such as Expert Systems with Applications, ISA Transactions, and IEEE Sensors Journal.
  • Citation Metrics: h-index of 5.
  • Patents: 6 patents published or under process.

Top Noted Publication:

In Situ Inversion of Lithium-Ion Battery Pack Unbalanced Current for Inconsistency Detection Using Magnetic Field Imaging

  • Journal: IEEE Transactions on Instrumentation and Measurement
  • Publication Date: 2024
  • DOI: 10.1109/TIM.2024.3472854
  • Contributors: Hang Wang, Lei Mao, Yongbin Liu, Jun Tao, Zhiyong Hu, Yuanyuan Zhou
  • Summary: This study introduces a novel approach leveraging magnetic field imaging to detect inconsistencies in lithium-ion battery pack currents, providing innovative solutions for enhanced performance evaluation and fault detection.

Feature Extraction Using Refined Composite Hierarchical Fuzzy Dispersion Entropy and its Applications to Bearing Fault Diagnosis

  • Journal: IEEE Sensors Journal
  • Publication Date: August 15, 2024
  • DOI: 10.1109/JSEN.2024.3422222
  • Contributors: Yuanyuan Zhou, Hang Wang, Yongbin Liu, Zhongding Fan, Xianzeng Liu, Zheng Cao
  • Summary: This paper develops a refined hierarchical fuzzy entropy method for feature extraction, enhancing the accuracy of bearing fault diagnosis.

A Multi-Scale Feature Extraction and Fusion Method for Diagnosing Bearing Faults

  • Journal: Journal of Dynamics, Monitoring and Diagnostics
  • Publication Date: August 7, 2024
  • DOI: 10.37965/jdmd.2024.560
  • Contributors: Zhixiang Chen, Hang Wang, Yuanyuan Zhou, Yang Yang, Yongbin Liu
  • Summary: Proposes a multi-scale approach for feature extraction and fusion, providing a comprehensive framework for diagnosing bearing faults with high reliability.

Intelligent Fault Diagnosis of Bearing Using Multiwavelet Perception Kernel Convolutional Neural Network

  • Journal: IEEE Sensors Journal
  • Publication Date: April 15, 2024
  • DOI: 10.1109/JSEN.2024.3370564
  • Contributors: Yuanyuan Zhou, Hang Wang, Yongbin Liu, Xianzeng Liu, Zheng Cao
  • Summary: Introduces a convolutional neural network architecture optimized with multiwavelet perception kernels for intelligent bearing fault diagnosis.

Degradation Indicator Construction Using Dual-Class Component Feature Fusion Recalibration for Bearing Performance Evaluation

  • Journal: IEEE Sensors Journal
  • Publication Date: 2023
  • DOI: 10.1109/JSEN.2023.3309630
  • Contributors: Yuanyuan Zhou, Hang Wang, Yongbin Liu, Xianzeng Liu, Zheng Cao, Yangyang Fu
  • Summary: This paper develops a dual-class component feature fusion method to recalibrate degradation indicators, improving the accuracy of bearing performance evaluation.

Conclusion:

Yuanyuan Zhou is a highly suitable candidate for the Best Researcher Award in Engineering. His innovative work in intelligent perception, performance evaluation, and fault diagnosis demonstrates a robust combination of academic excellence and practical problem-solving. His contributions, supported by a commendable publication record, patents, and peer recognition, reflect his dedication to advancing the field.

To maximize his potential, Zhou could focus on expanding his research collaborations, increasing interdisciplinary applications, and leading major research initiatives. With these enhancements, he is well-positioned to further solidify his status as a leading researcher in his domain.

 

 

Hien Thanh Le | Electrical Engineering Award | Best Researcher Award

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Dr. Hien Thanh Le, Electrical Engineering Award, Best Researcher Award

Doctorate at HUIT, Vietnam

Summary:

Dr. Hien Thanh Le is an accomplished electrical engineer with a diverse background in academia and industry. He holds a Doctoral degree in Electrical Engineering from the National Kaohsiung University of Science and Technology, Taiwan, where he pursued research in optical design. Prior to his doctoral studies, Dr. Le completed his Master’s degree in Electrical Engineering at the Ho Chi Minh City University of Technology and Education, Vietnam, focusing on clean development mechanism projects for manufacturing construction materials.

With extensive professional experience spanning over a decade, Dr. Le has served as a lecturer at Dong Nai Technology University, Vietnam, where he teaches courses in Power Plant Technology, Electrical System Operation and Control, and Engineering Technology. He has also contributed significantly to research in optical design, clean energy technologies, power system analysis and control, and sustainable development.

Professional Profile:

Scopus Profile

Google Scholar Profile

👩‍🎓Education & Qualification:

Bachelor of Engineer of Electrification and Power Supply:

  • Institution: LAC HONG University
  • Duration: October 2007 – October 2012
  • Major: Electrification and Power
  • GPA: 7.47

Master of Electrical Engineering:

  • Institution: HCMC University of Technology and Education
  • Duration: December 2012 – October 2015
  • Major: Electrical Engineering
  • Thesis Topic: “Set up clean development mechanism project file for some manufacturing of construction materials”
  • GPA: 6.59

Doctoral of Electrical Engineering:

  • Institution: National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan
  • Duration: September 2017 – September 2021
  • Major: Electrical Engineering
  • GPA: 4.00

Professional Experience:  

Dr. Hien Thanh Le has amassed significant professional experience in the field of electrical engineering, demonstrating a commitment to both academia and industry. Since 2013, Dr. Le has served as a lecturer at Dong Nai Technology University, where he has been actively involved in teaching a variety of subjects, including Power Plant Technology, Electrical System Operation and Control, Protection and Management of Electrical Systems, and Base M&E Design, among others. In addition to teaching, he has been engaged in pioneering research endeavors, exploring new technologies and contributing to the advancement of knowledge in his field. Dr. Le has also taken on the responsibility of managing the laboratory of technology, overseeing its operations and ensuring a conducive learning environment for students. Prior to his academic role, Dr. Le worked as a Design Engineer at Gen World Company, where he was involved in the design and development of electrical devices such as transformers, generators, motors, and power electronics. His expertise extends to the design of controllers utilizing microcontrollers, programmable logic controllers, digital signal processors, and electrical circuits. Through his combined experiences in academia and industry, Dr. Le has demonstrated a deep commitment to advancing the field of electrical engineering through education, research, and practical applications.

Research Interest:

Optical Design: Dr. Le is involved in research related to optical design, which involves the development and optimization of optical systems for various applications. This may include the design of lenses, mirrors, and other optical components used in imaging systems, sensors, and communication systems.

Clean Energy Technologies: Dr. Le is interested in exploring clean energy technologies, with a focus on renewable energy sources such as solar and wind power. His research may involve the design, optimization, and implementation of systems for harnessing renewable energy and integrating it into existing power grids.

Power System Analysis and Control: Dr. Le is engaged in research related to power system analysis and control, aiming to improve the efficiency, reliability, and stability of electrical power systems. This may involve the development of advanced control algorithms, grid optimization techniques, and predictive maintenance strategies.

Sustainable Development: Dr. Le is passionate about research that contributes to sustainable development goals, particularly in the context of energy and environmental sustainability. His research may involve the assessment of environmental impacts, lifecycle analysis of energy systems, and the development of sustainable technologies and practices.

Smart Grid Technologies: Dr. Le’s research interests also extend to smart grid technologies, which involve the integration of advanced communication, control, and monitoring systems into electrical power grids. His research may focus on optimizing grid operations, enhancing grid resilience, and enabling the efficient integration of renewable energy sources and distributed energy resources.

Publication Top Noted:

Design of a Society of Automotive Engineers Regular Curved Retroreflector for Enhancing Optical Efficiency and Working Area

  • Authors: LT Le, HT Le, J Lee, HY Ma, HY Lee
  • Published in: Crystals, Volume 8, Issue 12, Page 450, 2018

Design of Low-Glared LED Rear Light of Automotive for EU ECE Regulation by Use of Optimized Micro-Prisms Array

  • Authors: HT Le, LT Le, HY Liao, MJ Chen, HY Ma, HY Lee
  • Published in: Crystals, Volume 10, Issue 2, Page 63, 2020

ECE/SAE Dual Functional Superpin Plus Curved Reflex Reflector by Use of New Structured Corner Cubes

  • Authors: HT Le, LT Le, MJ Chen, TH Lam, HY Liao, GF Luo, YC Li, HY Lee
  • Published in: Applied Sciences, Volume 10, Issue 2, Page 454, 2020

Low-Glare Freeform-Surfaced Street Light Luminaire Optimization to Meet Enhanced Road Lighting Standards

  • Authors: J Lee, LT Le, HT Le, HY Liao, GZ Huang, HY Ma, CC Wen, YC Fang
  • Published in: International Journal of Optics, Volume 2020, Pages 1-12, 2020

Design of Counter Beam Tunnel Lights for CIE 88: 2004 Regulation in Threshold Zone

  • Authors: MJ Chen, HT Le, LT Le, WH Tseng, WY Lee, SY Chen, SY Chen, HY Liao
  • Published in: International Journal of Optics, Volume 2020, Pages 1-9, 2020