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Mr.Eustache Uwimana | Engineering | Best Researcher Award

PhD Researcher, Hebei University of Technology, China

Eustache Uwimana is a dedicated Ph.D. researcher and Electrical Electronics Engineer at Beichen, Tianjin, with a strong focus on innovative energy solutions. With a passion for tackling complex problems, Eustache aims to contribute to advancements in electrical engineering and energy consulting.

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Education 🎓

 

Eustache holds a Ph.D. in Electronics Information Engineering (expected graduation: 2025) from Hebel University of Technology, Beichen Campus, Tianjin, China. He also earned a Master’s in Engineering in Oil and Gas Technology from Kuban State University of Technology in 2015, and a Bachelor’s in Electrical Power Engineering from the National University of Rwanda in 2012.

Experience 💼

 

Currently a Ph.D. researcher at Beichen, Tianjin, Eustache has been involved in evaluating installer performance and coordinating with vendors for project materials since September 2019. His practical experience includes investigating customer complaints and implementing corrective actions to ensure quality in installations.

Research Interest 🔍

 

Eustache’s research interests lie in electrical load forecasting and machine learning applications within energy systems. His work focuses on enhancing forecasting accuracy for power demand, particularly in Rwandan power systems.

Award 🏆

 

Eustache received the prestigious Chinese Scholarship Counsel Award for his Ph.D. studies in 2019, alongside the Presidential Scholarship for his Master’s degree in Russia in 2012, recognizing his academic excellence and potential.

Publications Top Notes📚 : 

“Long-Term electrical load forecasting in Rwanda based on support vector machine enhanced with Q-SVM optimization kernel function.” Journal of Power and Energy Engineering, 11(08), 32-54. Link (2023).

“Medium-term electrical power load demand forecasting for smart grid of a Rwandan power system using machine learning methods.”

“A Novel Two Stage Hybrid Model Optimization with FS-FCRBM-GWDO for Accurate and Stable STLE.”Preprints 2024, 2024081852. Link (2024).

“A Short-Term Load Demand Forecasting: Levenberg Marquardt (LM), Bayesian Regularisation (BR), and Scaled Conjugate Gradient (SCG) Optimization Algorithm Review.”

Mr.Eustache Uwimana | Engineering | Best Researcher Award

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