Yue-Der Lin | Engineering | Best Researcher Award

Prof. Yue-Der Lin | Engineering | Best Researcher Award

Professor Feng Chia University/Department of Automatic Control Engineering Taiwan

🎓 Dr. Yue-Der Lin is a Professor at the Department of Automatic Control Engineering, Feng Chia University, Taiwan. With extensive experience in biomedical engineering, he specializes in biopotential amplifier design, adaptive signal processing, and EEG signal analysis. His research bridges biomedical and electronic engineering, contributing significantly to advancements in biopotential measurement and bioinformatics.

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Education

📘 Ph.D. in Electrical Engineering (Biomedical Engineering Program)
National Taiwan University, Taiwan (1992–1998)
📘 Master’s in Electrical Engineering (Biomedical Engineering & Electronic Circuit Programs)
National Taiwan University, Taiwan (1987–1989)
📘 Bachelor’s in Electrical Engineering (Control Program)
Chung Yuan Christian University, Taiwan (1983–1987)

Professional Experience

💼 Professor, Department of Automatic Engineering, Feng Chia University (2019–Present)
💼 Director, Department of Automatic Engineering (2016–2017)
💼 Director, Master’s Program of Biomedical Informatics and Biomedical Engineering (2014–2017)
💼 Visiting Scholar, Department of Electrical and Computer Engineering (2007)

Research Interests

🔬 Dr. Lin’s research focuses on:

  • Biopotential amplifier design
  • Adaptive signal processing
  • Biomedical signal analysis (EEG, EMG)
  • Bioinformatics systems
  • Advanced imaging techniques in biomedical engineering

Honors and Awards

🏆 Excellent Research Award, Feng Chia University (2005, 2007–2009, 2011–2019, 2021–2024)
🏆 Distinguished Scholar Award, National Science and Technology Council, Taiwan (2014–2015, 2018–2020, 2022–2024)
🏆 Albert Nelson Marquis Lifetime Achievement Award (2017–2018, 2020)
🏆 Marquis Who’s Who in the World (2008–2010, 2012–2020)
🏆 IBC Leading Engineers of the World (2008, 2013, 2015)

Publications Top Notes:

📚 Below are Dr. Yue-Der Lin’s selected publications with publication year, journal, and citation details:

Lin, Y.-D., Chong, F.-C., Sung, S.-M., et al. “The calculation of complexity in normal and apoplectic EEG signals.” Journal of the Chinese Institute of Engineers, Vol. 21, No. 5, pp. 585-594, 1998. Cited by 56

Lin, Y.-D., Wu, C.-P., et al. “An active comb filter structure for harmonic interference removal.” Journal of the Chinese Institute of Engineers, Vol. 21, No. 5, pp. 605-610, 1998. Cited by 40

Lin, Y.-D., et al. “Preamplifier with a second-order high-pass filtering characteristic.” IEEE Transactions on Biomedical Engineering, Vol. 46, No. 5, pp. 609-612, 1999. Cited by 95

Lin, Y.-D., et al. “An adaptive power-line interference removal technique for biopotential measurement.” Biomedical Engineering—Applications, Basis and Communications, Vol. 12, No. 1, pp. 24-32, 2000. Cited by 23

Lin, Y.-D., et al. “Comments on ‘Line patterns in the mosaic electric properties of human skin—A cross-correlation study’.” IEEE Transactions on Biomedical Engineering, Vol. 49, No. 3, pp. 274, 2002. Cited by 15

Use of acupressure to improve gastrointestinal motility in women after trans-abdominal hysterectomy

Aminoguanidine prevents the impairment of cardiac pumping mechanics in rats with streptozotocin and nicotinamide‐induced type 2 diabetes

A novel approach for decomposition of biomedical signals in different applications based on data-adaptive Gaussian average filtering

Guangze Pan | Engineering | Best Paper Award

Mr. Guangze Pan | Engineering | Best Paper Award

Senior Engineer China Electronic Product Reliability and Environmental Testing Research Institute China

Guangze Pan is a Senior Engineer at the China Electronic Product Reliability and Environmental Testing Research Institute. He earned his master’s degree from Beihang University and has accumulated over ten years of experience in reliability engineering. Throughout his career, he has contributed to over 20 major research projects, many of which were funded by the National Natural Science Foundation of China and the National Key Research and Development Program. Guangze has published more than 20 high-level papers and holds 17 invention patents. His work is highly regarded in the field of reliability testing and evaluation. 🛠️📑

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Education 🎓

Guangze Pan completed his master’s degree at Beihang University, a leading institution in China. This foundation has equipped him with extensive knowledge and expertise in reliability engineering, which he has built upon throughout his career.

Experience 💼

With over a decade of experience, Guangze has worked on numerous high-profile projects, contributing significantly to the development of advanced reliability testing technologies. He has been instrumental in the research and application of parallel reliability testing techniques, improving testing efficiency by 83%. This has positively impacted industries such as industrial robotics, where his innovations have significantly enhanced reliability, increasing the mean time between failures from 6,000 hours to 80,000 hours.

Research Interests 🔬

Guangze’s primary research interest lies in reliability testing and evaluation, particularly in multi-component, multi-stress, and multi-profile systems. He focuses on rapid reliability testing of complex systems, aiming to improve efficiency and precision. His work has been vital in elevating the reliability of industrial robots and other critical systems.

Awards 🏆

Guangze Pan’s contributions have been recognized through prestigious awards, including the second prize of the Science and Technology Award from the China Instrument Society. His research has also been appraised by the Guangdong Society of Mechanical Engineering, where it was acknowledged for reaching international leading levels.

Publications Top Notes: 📚

Guangze has published over 20 research papers in high-impact journals, with significant contributions in reliability engineering. He has an h-index of 27, and his work has influenced the development of cutting-edge technologies. For more information on his publications, visit his ResearchGate profile.

A novel machine learning-based imputation strategy for missing data in step-stress accelerated degradation test

Study on Simulation Analysis of Secondary Board Card with Multi-Physical Field Coupling

A reliability evaluation method of complex electromechanical products based on the multi-stress coupling acceleration model

A reliability analysis method based on the mixed correlated competition model considering multi-performance degradation and sudden failures

A Novel Machine Learning-Based Imputation Strategies for Missing Data in Step-Stress Accelerated Degradation Test

Fault-tolerant Scheduling Method Based on Imprecise Calculation for Real-time System of Aviation Equipment

A Reliability Evaluation Method for Multi-performance Degradation Products Based on Accelerated Degradation Testing