

Dr. V. B. Murali Krishna
Department of Electrical Engineering, National Institute of Technology-Andhra Pradesh
Dr. V. B. Murali Krishna is a certified Chartered Engineer (CEng) from The Institution of Engineers (India). He has a doctorate in electrical engineering from the Central University of Karnataka. Currently, he is part of the teaching faculty at the National Institute of Technology-Andhra Pradesh (NIT-Andhra Pradesh), India.Beyond his academic and research activities, Dr. Krishna holds multiple editorial roles, including associate editor at e-Prime - Advances in Electrical Engineering, Electronics and Energy and topical editor at Contemporary Mathematics. He is also an editorial board member for Discover Energy. An active reviewer for over 25 international journals and five conference series, he has received the Reviewer of Excellence award. His research has earned three Best Paper awards at international conferences, and his PhD thesis received the Best Thesis award from IEEE Bangalore. Additionally, he has organized three national conferences, chaired sessions at international conferences (2023–24), and has over 50 published or presented academic articles.His research focuses on renewable energy, smart grids, electric vehicles, IoT, adaptive technologies, system optimization, and AI-driven data analysis.

Rajesh Cheruku
School of Engineering, Dayananda Sagar University
Dr. Rajesh Cheruku has a doctorate in physics from Pondicherry University, India. Starting in 2015, he held the position of assistant professor at Yeungnam University in South Korea, where he continued to work until 2020. In 2021, he was appointed assistant professor at the Central University of Karnataka, India. Since 2022, he has been an assistant professor at Dayananda Sagar University, India. Dr. Cheruku serves as a reviewer for several prestigious journals and has published more than 45 academic articles. His interests include system control, security, and optimization in renewable energy, battery storage, EV charging, smart alerts, and IoT-driven renewable adaptive technologies.

İskender Akkurt
Suleyman Demirel University
Dr. İskender Akkurt is a professor at the Faculty of Engineering and Natural Sciences, Department of Physics at Süleyman Demirel University, Turkey. He received his doctorate from the University of Glasgow in 1998. He has published over 160 articles in reputed international journals, presented more than 50 papers at international scientific meetings, contributed to conference proceedings, and authored two books.

Kenneth E. Okedu
School of Information Technology and Engineering, Melbourne Institute of Technology
Dr. Kenneth Okedu is a researcher and professor specializing in renewable energy and power systems. He earned his PhD from the Kitami Institute of Technology, Japan, and was a research fellow in the Department of Electrical and Computer Engineering at MIT, USA. He has held academic and visiting faculty positions in Nigeria, Oman, and Turkey. A prolific researcher, Dr. Okedu serves as an editor for multiple engineering journals and was recognized as a top 1% peer reviewer in Engineering by Publons. He was also among Stanford University's top 2% of most cited researchers globally. Currently, he is a researcher at Victoria University, Melbourne, and a faculty member at the Melbourne Institute of Technology. In addition, he works full-time as a Renewable and Power Systems Advisor at Vysus Group, Melbourne, Australia. His research focuses on power system stability, wind energy integration, and renewable energy storage.
As the globe faces rising environmental difficulties, the switch to sustainable energy solutions has become more crucial than ever. Data-driven decision-making systems play a vital role in promoting eco-friendly energy solutions by enhancing the efficiency, accuracy, and adaptability of modern energy infrastructures. These models encourage innovation in sustainable energy development by leveraging cutting-edge technologies such as artificial intelligence, machine learning, deep learning, cybersecurity, smart sensing, image processing, control and optimization, energy management systems, and smart grids. Furthermore, the seamless integration of locally accessible renewable energy sources into electric vehicles via smart grids stimulates community-driven energy solutions and promotes energy fairness.
This Methods Collection intends to study developing decision-making frameworks to assist green energy systems and sustainable development. By addressing critical research gaps, the collection introduces new methodologies and applications that refine decision-making processes essential for the growth of sustainable energy solutions.
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2026
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Surya Prakasa Rao Reddi1, Srinivasa Rao P2, S Suguna Mallika3, Dileep Pulugu4, Mantri Gayatri5, Vimala Kumari G6
1Department of Electronics and Communication Engineering, Gayatri Vidya Parishad College of Engineering (A), 2Department of Computer Science and Engineering, MVGR College of Engineering (A), 3Department of Computer Science and Engineering, CVR College of Engineering, 4Department of Computer Science and Engineering, Malla Reddy College of Engineering and Technology, 5Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, 6Department of Electronics and Communication Engineering, MVGR College of Engineering
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2026
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1Institute of Translational Medicine Zhuhai People's Hospital Affiliated with Jinan University, 2Department of Food Science and Engineering, Institute of Food Safety and Nutrition, Jinan University, 3The Affiliated Guangdong Second Provincial General Hospital of Jinan University, 4State Key Laboratory of Bioactive Molecules and Druggability Assessment, The Biomedical Translational Research Institute, Health Science Center (School of Medicine), Jinan University
Characterizing multiphase flow in porous media by polynomial physical neural network
Yunqi Jiang1
1Petrochina Southwest Oil and Gas Field Company