Haoming Ma | Energy | Best Researcher Award

Dr. Haoming Ma | Energy | Best Researcher Award

University of Texas at Austin | United States

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Scopus

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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)

 

 

Esmat Zaidan | Energy | Best Researcher Award

Dr. Esmat Zaidan | Energy | Best Researcher Award

Hamad Bin Khalifa University | Qatar

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Scopus

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Early Academic Pursuits

Dr. Esmat Zaidan embarked on her academic journey with a Master's degree in Urban Planning and Design from Birzeit University. She further pursued a Master of Economic Development and later a Ph.D. in Geography and Environmental Management from the University of Waterloo, Canada, completing her educational milestones by 2011.

Professional Endeavors

With a rich background in academia and research, Dr. Zaidan held various positions, including Associate Professor of Policy, Planning, and Development at Qatar University and Assistant Professor of Urban Planning at the United Arab Emirates University. She also contributed significantly to organizations like the World Bank, NORAD, and UNDP, gaining substantial experience in global development challenges and policy implementation.

Contributions and Research Focus

Dr. Zaidan's interdisciplinary research focuses on sustainable development policy, climate change mitigation, energy transition, and smart city initiatives. Her expertise lies in data-driven policy making for enhancing sustainability and resilience, particularly in residential buildings. Her publications and funded research projects underscore her commitment to advancing sustainable development and shaping future-oriented policies.

Accolades and Recognition

With over 60 articles published in top-tier journals and numerous research grants awarded, Dr. Zaidan is recognized as an expert in her field. She has received accolades for her contributions to academia and policy development, showcasing her dedication to fostering sustainable solutions.

Impact and Influence

Dr. Zaidan's impact extends beyond academia, as evidenced by her involvement in shaping national development strategies such as the Qatar National Development Strategy (QNDS). Her ability to foster collaborations and facilitate knowledge exchange has influenced policy-making processes, driving progress towards sustainable development goals.

Legacy and Future Contributions

Dr. Zaidan's legacy lies in her multifaceted contributions to academia, research, and policy implementation. Her ongoing work, including edited volumes and collaborations, promises to further advance the fields of sustainable development, public policy, and urban planning. Through her continued efforts, she aims to leave a lasting impact on shaping resilient and sustainable communities for future generations.

Notable Publications

Achieving energy justice: The role of supervisory and compliance mechanisms in global frameworks and the international community 2024

Modeling and forecasting electricity consumption amid the COVID-19 pandemic: Machine learning vs. nonlinear econometric time series models 2023 (4)

Exploring internet inclusivity and effectiveness of e-learning initiatives during the pandemic – a comparative analysis 2023

The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar 2022 (15)

Motivation, preference, socioeconomic, and building features: New paradigm of analyzing electricity consumption in residential buildings 2022 (21)

 

 

 

Lei Wang | Energy | Innovation in Publishing Award

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)

 

 

 

Vikash Saini | Energy | Editorial Board Member

Mr. Vikash Saini | Energy | Editorial Board Member

MNIT, Jaipur | India

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Google Scholar

Early Academic Pursuits

Vikash Saini, hailing from MNIT Jaipur, India, embarked on an academic journey marked by excellence. Graduating in Electrical Engineering and subsequently earning an M.Tech in Power Systems, he exhibited a keen interest in cutting-edge domains.

Professional Endeavors

Vikash's professional trajectory includes roles at esteemed institutions such as IIT Kanpur, Poornima College of Engineering, and significant contributions in seismic data processing at BP. He pursued a Ph.D. at MNIT Jaipur, showcasing a commitment to advancing knowledge.

Contributions and Research Focus

His expertise spans diverse areas like RE forecasting, energy storage, battery degradation models, local energy markets, and blockchain technology. Vikash has led projects focusing on smart distributive systems, EV charging infrastructure, and the impact of electric mobility.

Accolades and Recognition

Vikash's research has earned recognition with publications in renowned journals, including Elsevier. His work on short-term wind speed forecasting and optimal battery sizing demonstrates his innovative contributions to the field.

Impact and Influence

Vikash's influence extends to various domains, evident in his work on peer-to-peer energy trading, multi-agent systems, and cloud energy storage. His projects have addressed critical aspects like energy security, carbon footprint, and optimal power flow in distribution networks.

Legacy and Future Contributions

With a solid foundation in programming (C, Python) and tools like Matlab and GAMS, Vikash has positioned himself as a thought leader. His commitment to renewable energy, blockchain, and smart grids showcases a legacy focused on sustainability and technological innovation.

Notable Publications

Short term forecasting based on hourly wind speed data using deep learning algorithms 2020 (25)

Optimal energy management system for residential buildings considering the time of use price with swarm intelligence algorithms 2022 (26)

Cloud Energy Storage Systems for Consumers and Prosumers in Residential Microgrids 2020 (8)

Cloud Energy Storage Based Embedded Battery Technology Architecture for Residential Users Cost Minimization 2022 (14)

Learning Approach for Energy Consumption Forecasting in Residential Microgrid 2022 (6)