Weijun Wang | Engineering | Best Researcher Award

Published on by Popular Scientist

Dr. Weijun Wang | Engineering | Best Researcher Award

Student Changchun University of Technology China

🌟 Weijun Wang (王威珺) is a researcher in the field of Statistics, currently pursuing a Ph.D. at Changchun University of Technology, China. With expertise spanning fault diagnosis, data-driven designs, and dynamic systems, Weijun Wang has made significant contributions to high-speed train traction systems and other advanced engineering applications.

Profile

Scopus

Education

🎓 Weijun Wang’s academic journey includes:

  • Ph.D. in Statistics (2021–Present): Changchun University of Technology.
  • Master’s in Information and Communication Engineering (2018–2021): Changchun University of Technology.
  • Bachelor’s in Electronic Information Engineering (2014–2018): Changchun University of Technology.

Experience

👩‍🔬 Weijun Wang has extensive experience in developing innovative fault detection methods, dynamic system models, and data-driven algorithms. Collaborating on multidisciplinary projects, she has co-authored several impactful journal and conference papers.

Research Interests

🔬 Weijun Wang’s research focuses on:

  • Fault detection and diagnosis.
  • Data-driven modeling for high-speed train traction systems.
  • Dynamic systems, robust designs, and performance prediction.

Awards

🏆 First Prize: National Finals at RAICOM, 2024.
🏅 Innovation Award: 3rd China Urban Rail Transit Science and Technology Innovation Competition, 2022.

Publications

A Martingale Posterior-Based Fault Detection and Estimation Method for Electrical Systems of Industry

Dynamic Fault Detection Method of Traction Systems in High-Speed Trains Based on Joint Observer

Data-Driven Robust Designs of Performance Prediction and Its Application in High-speed Trains

Enhanced Fault Diagnosis Using Broad Learning for Traction Systems in High-Speed Trains

State Estimation with Partial Random Walk

State-degradation-oriented fault diagnosis for high-speed train running gears system

Fault prediction of high-speed train running gears based on hidden markov model and analytic hierarchy process

Multi-sensor system filtering and fault detection under unbiased constraint and colored measurement noise

Yusuf Alper KAPLAN | Engineering | Best Researcher Award

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Prof. Yusuf Alper KAPLAN | Engineering | Best Researcher Award

Prof. Osmaniye Korkut Ata Unv. Turkey

Dr. Yusuf Alper Kaplan is a Professor of Energy Systems Engineering at Osmaniye Korkut Ata University in Turkey. He has a distinguished career in renewable energy, specializing in solar and wind energy modeling, estimation, and system performance. With over two decades of experience, Dr. Kaplan has contributed to advancing energy systems through innovative methodologies and predictive models.

Profile

Google scholar

Education 🎓

  • Bachelor’s in Electrical and Electronics Engineering, Gaziantep University, 2002
  • Master’s in Electrical and Electronics Engineering, Çukurova University, 2008
  • Ph.D. in Electrical and Electronics Engineering, Anadolu University, 2014

Professional Experience 💼

  • Lecturer (2004-2009) at Çukurova University
  • Research Assistant (2010-2014) at Anadolu University
  • Assistant Professor (2014-2018), Associate Professor (2018-2023), and Professor (2023-present) at Osmaniye Korkut Ata University
  • Head of Department of Energy Systems Engineering (2019-2020)
  • Director of the Continuing Education Centre (2020-present)

Research Interests 🔬

Dr. Kaplan’s research focuses on renewable energy, especially solar and wind energy systems. His work involves developing statistical and computational models for solar radiation forecasting, wind energy assessment, and performance optimization of renewable energy sources in varying environmental conditions.

Awards and Recognitions 🏆

Dr. Kaplan has been honored for his contributions to renewable energy and academic excellence. His achievements include national and international recognitions for advancements in energy system performance modeling and contributions to sustainable energy solutions.

Publications Top Notes: 📚

Kaplan, Y. A. (2024). Forecasting of global solar radiation: A statistical approach using simulated annealing algorithm. Engineering Applications of Artificial Intelligence, 136, 109034. (Cited by 15)

Kaplan, A. G., & Kaplan, Y. A. (2024). Using of the Weibull distribution in developing global solar radiation forecasting models. Environmental Progress & Sustainable Energy. (Cited by 10)

Kaplan, Y. A. (2023). Development of backpropagation algorithm for estimating solar radiation: A case study in Turkey. Revue Roumaine des Sciences Techniques, 68(3), 313-316. (Cited by 8)