Padmini Sankaramurthy | Energy | Research Excellence Award

Published-on by Indian Scientist

Dr. Padmini Sankaramurthy | Energy | Research Excellence Award

SRM Institute of Science and Technology | India

Dr. S. Padmini is an accomplished academic and researcher with a strong foundation in Electrical and Electronics Engineering, advanced training in Power Systems Engineering, and doctoral work centered on intelligent algorithms for hydrothermal scheduling, further strengthened by an ongoing postdoctoral fellowship in multidisciplinary AI applications. With extensive teaching and research experience in a premier institution, she has contributed significantly to curriculum development, research supervision, academic leadership, and large-scale institutional activities. Her scholarly output includes publications indexed in major databases, patents, major project proposals, international collaborations, and diverse technical contributions across intelligent systems, power systems optimization, energy economics, and AI-driven engineering solutions. She has delivered numerous courses, created substantial digital learning resources, and guided students at multiple academic levels. Her research has earned citations totalling 341, along with an h-index of 10 and an i10-index of 10, demonstrating meaningful global impact. She is recognized for excellence through multiple awards, including distinguished scientific honours, innovation-driven recognitions, and accolades for academic contributions. Her ongoing collaborations across global universities reflect her commitment to advancing multidisciplinary research. Dr. Padmini’s work continues to integrate engineering intelligence, sustainable energy solutions, and advanced computational methods to support emerging technological needs and societal progress.

Profiles: Google Scholar | Orcid | Scopus

Featured Publication

Jeevadason, A. W., Padmini, S., Bharatiraja, C., & Kabeel, A. E. (2022). A review on diverse combinations and Energy-Exergy-Economics (3E) of hybrid solar still desalination. Desalination, 527, 115587.

Rebecca, B., Kumar, K. P. M., Padmini, S., Srivastava, B. K., Halder, S., & Boopathi, S. (2024). Convergence of Data Science-AI-Green Chemistry-Affordable Medicine: Transforming Drug Discovery. In Handbook of Research on AI and ML for Intelligent Machines and Systems (pp. 348–373).

Venkatesh, B., Sankaramurthy, P., Chokkalingam, B., & Mihet-Popa, L. (2022). Managing the demand in a micro grid based on load shifting with controllable devices using hybrid WFS2ACSO technique. Energies, 15(3), 790.

Lakshmi, K., Amaran, S., Subbulakshmi, G., Padmini, S., Joshi, G. P., & Cho, W. (2025). Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images. Scientific Reports, 15(1), 690.

Sankaramurthy, P., Chokkalingam, B., Padmanaban, S., Leonowicz, Z., … Padmini, S. (2019). Rescheduling of generators with pumped hydro storage units to relieve congestion incorporating flower pollination optimization. Energies, 12(8), 1477.

Pankaj Kumar Dubey | Electrical engineering | Young Researcher Award

Published-on by Indian Scientist

Mr. Pankaj Kumar Dubey | Electrical engineering | Young Researcher Award

Kamla Nehru Institute of Technology Sultanpur | India

Pankaj Kumar Dubey is an active researcher whose work spans healthcare analytics, digital technologies, and emerging computational approaches. His research focuses on applying artificial intelligence and deep learning models to clinical decision-making, medical image analysis, and personalized treatment strategies. He has contributed to studies involving predictive modelling, pattern detection, and optimization frameworks that support improved diagnostic accuracy in healthcare systems. His work also explores the integration of digital tools, including blockchain and IoT-based solutions, to enhance transparency, data security, and efficiency in medical and industrial environments. His publications reflect multidisciplinary engagement, combining data science, biomedical engineering, and informatics to address contemporary challenges in healthcare and technology-driven ecosystems. He has participated in conferences and workshops presenting findings related to algorithmic optimization, intelligent systems, and AI applications in real-world scenarios. His research output includes peer-reviewed journal articles, conference presentations, and book chapters focusing on advanced computational methods. He has also collaborated on projects that utilize machine learning classifiers, neural networks, and hybrid models for problem-solving across domains such as supply chain management, disease prediction, and smart monitoring systems. His overall research demonstrates a strong commitment to innovation and the practical deployment of technology-enabled solutions that contribute to societal and scientific advancement.

Profile: Google Scholar | Orcid

Featured Publications

Singh, B., & Dubey, P. K. (2022). Distributed power generation planning for distribution networks using electric vehicles: Systematic attention to challenges and opportunities. Journal of Energy Storage, 48, 104030.

Yadav, S., Sudman, M. S. I., Dubey, P. K., Srinivas, R. V., Srisainath, R., & Devi, V. C. (2023). Development of a GA–RBF based model for penetration of electric vehicles and its projections. In 2023 International Conference on Self Sustainable Artificial Intelligence (ICSSAI).

Singh, B., Dubey, P. K., & Singh, S. N. (2022). Recent optimization techniques for coordinated control of electric vehicles in super smart power grids network: A state of the art. In 2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON).

Dubey, P. K., Singh, B., Kumar, V., & Singh, D. (2024). A novel approach for comparative analysis of distributed generations and electric vehicles in distribution systems. Electrical Engineering, 106(3), 2371–2390.

Negi, P., Dubey, P. K., Kumar, S., Palodkar, A. V., & Kumar, A. (2023). Experimental investigation of waste polyolefin composition on thermal conversion into petroleum-derived products. Fuel, 348, 128466.

Rajesh Bhagat | Engineering | Best Researcher Award

Published-on by Indian Scientist

Dr. Rajesh Bhagat | Engineering | Best Researcher Award

Yeshwantrao Chavan College of Engineering, Nagpur| India

Dr. Rajesh Madhukar Bhagat is an accomplished academician and researcher in the field of Mechanical Engineering, recognized for his significant contributions to manufacturing and industrial engineering. With an h-index of 7, over 42 documents, and more than 170 citations, his research exhibits a consistent impact in the scientific community. He holds a Ph.D. in Mechanical Engineering and has extensive teaching and research experience across reputed institutions, where he has mentored students and guided projects in areas such as production engineering, material science, and sustainable manufacturing. His academic endeavors focus on computer-aided design, optimization of manufacturing processes, renewable energy integration, and mechanical systems innovation. Dr. Bhagat has presented several papers at national and international conferences and published his work in reputed peer-reviewed journals. He has been recognized with multiple academic and research awards for his contributions to engineering education and innovation. With a strong blend of teaching excellence and research proficiency, Dr. Bhagat continues to inspire the next generation of engineers and researchers. His dedication toward advancing industrial technologies and promoting sustainable engineering solutions underscores his professional vision and impact in the field.

Profile: Google Scholar

Featured Publications

Agrawal, V., Bhagat, R., & Thikare, N. (2014). Impact of domestic sewage for irrigation on properties of soil. International Journal of Research Studies in Science, Engineering and Technology.

Bahoria, B. V., Pande, P. B., Dhengare, S. W., Raut, J. M., Bhagat, R. M., Shelke, N. M., & others. (2024). Predictive models for properties of hybrid blended modified sustainable concrete incorporating nano-silica, basalt fibers, and recycled aggregates: Application of advanced machine learning algorithms. Nano-Structures & Nano-Objects, 40, 101373.

Pande, P. B., Dhengare, S. W., Raut, J. M., Bhagat, R. M., Bahoria, B. V., Shelke, N., & others. (2025). Integrated hybrid machine learning techniques and multiscale modeling towards evaluating the influence of nano-material on strength of concrete. Multiscale and Multidisciplinary Modeling, Experiments and Design, 8(1), 26.

Dhengare, S., Sharma, R. L., Sobti, J., Gajbhiye, A. R., & Bhagat, R. (2020). Binary concrete expansion by means of copper slag, fly ash, sugarcane bagasse ash, and rice husk ash as partial replacement of cement. International Journal of Advanced Science and Technology, 29(7), 9973–9993.

Sharma, S., Bhagat, R., & Kanjilal, B. (1999). Community managed health financing: A strategy for achieving livelihood security and sustainable health impact. New Delhi: CARE-India.