Koat Jing Riek | Engineering | Editorial Board Member

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Mr. Koat Jing Riek | Engineering | Editorial Board Member 

Gambella University | Ethiopia

Author Profile

Orcid

🎓 Early Academic Pursuits

Mr. Koat Jing Riek began his academic journey with a Bachelor of Science in Mechanical Engineering from Hawassa University in 2015. He further honed his expertise by earning an MSc in Sustainable Energy Engineering from Jimma Institute of Technology, where his thesis focused on a GIS-based site suitability analysis of non-wooden biomass solar-driven briquetting plants in Gambella Regional State. His academic path reflects a deep-rooted interest in sustainable energy solutions tailored to regional needs.

💼 Professional Endeavors

Mr. Koat has carved a multidimensional career in academia, consultancy, and public service. Since 2017, he has served as a Senior Lecturer at Gambella University, leading vital research and community development initiatives in the fields of energy and environment.

His professional journey includes key roles such as:

  • Technical Expert at Minilek Kefale Economic Development Consultancy, where he assessed biomass resources and facilitated cooperative development.

  • Consulting Engineer for the Development Response to Displacement Impacts Project (DRDIP), delivering training and designing energy solutions for remote communities.

  • Fuel Administrator at Ethio Telecom and Office Engineer-Energy at Gambella Water and Energy Bureau.

  • WASH Foreman with NRC, ensuring sanitation and hygiene in refugee camps.

🔬 Contributions and Research Focus

Mr. Koat’s research and fieldwork bridge the gap between academia and community needs. His focus lies in:

  • Biomass energy systems and briquetting plant development

  • Improved cook stoves and solar energy solutions

  • Community-based training on climate change and environmental protection

  • Technical specification generation for sustainable energy products

His published work in the journal "The Future of Energy, Power and Environment" showcases his scientific rigor and commitment to evidence-based solutions.

🏅 Accolades and Recognition

Mr. Koat’s dedication to sustainable development has been widely recognized:

🏆 Certificates of appreciation for training delivery on solar irrigation and improved cook stoves
🏆 Awarded by DRDIP and Minilek Kefale Consultancy for technical expertise in community empowerment
🏆 Certified in GIS mapping, electromechanical troubleshooting, and water safety planning by institutions like UNHCR and Jimma Institute of Technology

🌍 Impact and Influence

Mr. Koat’s efforts have directly improved the livelihoods of communities in Gambella Region, especially through:

🌱 Establishing cooperatives for clean energy products
🔋 Training local stakeholders on solar technologies and energy efficiency
🏘️ Empowering underserved populations to adopt renewable energy systems

He stands as a catalyst for sustainable development through practical engineering, grassroots engagement, and academic leadership.

🔮 Legacy and Future Contributions

Looking ahead, Mr. Koat aims to scale sustainable energy initiatives across Ethiopia and beyond. His long-term vision is to bridge academia, policy, and community innovation to combat climate change and energy poverty. Through ongoing mentorship, research, and consultancy, Mr. Koat Jing Riek is poised to inspire a new generation of engineers and changemakers committed to a greener, more resilient future.

Publications

📄 Multi-criteria decision analysis using GIS in assessing suitability for a solar-powered biomass briquetting plant in the Gambella region, Ethiopia

Authors: Koat Jing Riek, Wondwossen Bogale Eremed

Journal: Trees, Forests and People

Year: 2025

Haoming Ma | Energy | Best Researcher Award

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Dr. Haoming Ma | Energy | Best Researcher Award

University of Texas at Austin | United States

Author profile

Scopus

Orcid

Early Academic Pursuits

Dr. Haoming Ma's academic journey began with a Bachelor's in Energy Engineering, complemented by minors in Environmental Engineering and Energy Business and Finance. He pursued his passion further, earning a Master's in Energy and Mineral Engineering, exploring the impacts of blackout cost recovery on stock behavior among electric utilities. His academic pursuits culminated in a Ph.D. in Chemical and Petroleum Engineering, focusing on data-driven carbon dioxide enhanced oil recovery models and their applications.

Professional Endeavors

Dr. Ma's professional journey encompasses diverse roles, from a Sessional Instructor at the Schulich School of Engineering to a Postdoctoral Fellow at the Energy Emissions Modeling and Data Lab, University of Texas at Austin. He also served as a Postdoctoral Research Associate at the Department of Chemical & Petroleum Engineering, University of Calgary. His research interests span reservoir simulation, system-level modeling, machine learning applications, and life cycle assessment.

Contributions and Research Focus

Dr. Ma's research integrates system modeling, data analytics, economic, and policy analysis to address economic and environmental challenges in energy systems and climate change mitigation. He has led and contributed to numerous research projects, focusing on CO2 capture, utilization, and sequestration, as well as unconventional resources recovery and hydrogen production and storage. His work provides a scientific foundation for technology and policy development towards environmental sustainability and carbon neutrality.

Accolades and Recognition

Dr. Ma's contributions have been recognized through various awards, including the Alberta Graduate Excellence Scholarship and the Chemical & Petroleum Engineering Graduate Excellence Award. He has also received accolades for his teaching excellence, including the Outstanding Graduate Teaching Assistant Award.

Impact and Influence

Dr. Ma's research publications, peer-reviewed articles, and conference proceedings demonstrate his significant impact on the field of energy and environmental engineering. His innovative approaches to techno-economic analysis and life cycle assessment contribute to shaping sustainable energy solutions globally.

Legacy and Future Contributions

Dr. Ma's leadership roles, professional services, and academic mentoring reflect his commitment to advancing the field and nurturing the next generation of energy leaders. His ongoing research and collaborations aim to drive further innovations in energy technology and policy, leaving a lasting legacy in the pursuit of environmental sustainability and carbon neutrality.

Notable Publications

Technical analysis of a novel economically mixed CO2-Water enhanced geothermal system 2024

Comparative data-driven enhanced geothermal systems forecasting models: A case study of Qiabuqia field in China 2023

Thermo-economic optimization of an enhanced geothermal system (EGS) based on machine learning and differential evolution algorithms 2023

Numerical simulation of bitumen recovery via supercritical water injection with in-situ upgrading 2022 (12)

Optimized schemes of enhanced shale gas recovery by CO2-N2 mixtures associated with CO2 sequestration 2022 (21)

 

 

Lei Wang | Energy | Innovation in Publishing Award

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Dr. Lei Wang | Energy | Innovation in Publishing Award

Tsinghua University | China

Author Profile

Orcid

Early Academic Pursuits

Lei Wang embarked on his academic journey, earning a Bachelor's degree in Electrical Engineering from Yangtze University in 2015. He furthered his studies, completing a Master's degree at Hubei University of Technology in 2019 and earning his Ph.D. from Wuhan University in Electrical Engineering in 2023.

Professional Endeavors

Lei Wang delved into the realm of academia, contributing significantly to various research projects. His roles included postdoctoral research at Tsinghua University, focusing on machine learning applications in battery prognostics and health management. He demonstrated his expertise in anomaly detection, safety assessment, and predictive modeling for battery systems.

Contributions and Research Focus

Lei Wang made substantial contributions to the "Power IoTs" project, focusing on deep reinforcement learning for adaptive uncertainty economic dispatch in power systems. His innovative models addressed the complexities of economic dispatch, showcasing adaptability to uncertain conditions, particularly in renewable energy integration scenarios.

Accolades and Recognition

Lei Wang received recognition for his pivotal role in developing a deep reinforcement learning-based approach, enhancing economic dispatch in power systems. His work contributed to grid reliability and efficiency, demonstrating practical applicability in real-world scenarios, particularly in Tianjin's Binhai New Area.

Impact and Influence

Lei Wang's research has left a lasting impact on the field, advancing the understanding of power system optimization. His work not only contributes to academic knowledge but also has practical implications for improving the efficiency and reliability of power delivery and consumption.

Legacy and Future Contributions

Lei Wang's legacy includes pioneering work in machine learning applications for battery systems and economic dispatch in power systems. Looking ahead, his expertise in artificial intelligence, spatiotemporal correlation modeling, and power equipment diagnosis positions him as a key contributor to the evolving landscape of energy research. As an emerging leader in the field, Lei Wang is poised to continue making groundbreaking contributions to the energy sector.

Notable Publications

An Unsupervised Approach to Wind Turbine Blade Icing Detection Based on Beta Variational Graph Attention Autoencoder 2023

Wind turbine blade icing risk assessment considering power output predictions based on SCSO-IFCM clustering algorithm 2024

A novel approach to ultra-short-term multi-step wind power predictions based on encoder–decoder architecture in natural language processing 2022 (18)

M2STAN: Multi-modal multi-task spatiotemporal attention network for multi-location ultra-short-term wind power multi-step predictions 2022 (22)

M2TNet: Multi-modal multi-task Transformer network for ultra-short-term wind power multi-step forecasting 2022 (19)