Kapil Dev Mahato | Organic Solar Cell | Best Researcher Award

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Best Researcher Award

Kapil Dev Mahato
Affiliation National Institute of Technology Jamshedpur
Country India
Scopus ID 57886400800
Documents 13
Citations 154
h-index 7
Subject Area Organic Solar Cell
Event International AI Data Scientists Award
ORCID 0000-0001-8448-2729

Kapil Dev Mahato
National Institute of Technology Jamshedpur

Kapil Dev Mahato is a researcher affiliated with the National Institute of Technology Jamshedpur, India, whose academic work focuses on organic solar cell technologies, renewable energy materials, and photovoltaic device development. His research activities contribute to the advancement of sustainable energy solutions through investigations into high-performance photovoltaic materials and energy conversion systems. With a growing publication portfolio and measurable citation impact, his work demonstrates continued engagement with emerging challenges in renewable energy research. Through interdisciplinary collaborations and scientific dissemination, he contributes to the broader objective of developing efficient, scalable, and environmentally responsible solar technologies.[1]

Abstract

This article presents an overview of the academic achievements and research contributions of Kapil Dev Mahato in the area of organic solar cells. His scholarly activities emphasize renewable energy technologies, photovoltaic materials, and sustainable energy conversion systems. Through peer-reviewed publications and recognized research outputs, he has contributed to scientific discussions surrounding the development of efficient solar energy devices and advanced functional materials.[2]

Keywords

Organic Solar Cells, Renewable Energy, Photovoltaics, Energy Materials, Solar Devices, Sustainable Technology, Thin Film Electronics, Green Energy.

Introduction

The increasing demand for sustainable energy has accelerated research into next-generation photovoltaic technologies. Organic solar cells have gained considerable attention because of their flexibility, lightweight characteristics, and potential for cost-effective production. Researchers worldwide continue to explore advanced materials and device architectures to improve efficiency and stability. Within this context, Kapil Dev Mahato’s research activities contribute to ongoing developments in organic photovoltaic science and renewable energy engineering.[3]

Research Profile

Kapil Dev Mahato is associated with the National Institute of Technology Jamshedpur and maintains an active research profile in the field of organic solar cell technology. According to available scholarly metrics, he has authored 13 indexed publications that have collectively received 154 citations and contributed to an h-index of 7. These indicators reflect consistent research productivity and scholarly engagement within the scientific community.[1]

Research Contributions

  • Research on advanced organic semiconductor materials for photovoltaic applications.
  • Development of strategies for improving solar cell efficiency and device stability.
  • Contribution to renewable energy research through scientific publications and collaborative studies.
  • Investigation of sustainable materials suitable for next-generation solar energy systems.

Publications

The research portfolio of Kapil Dev Mahato includes peer-reviewed journal articles focusing on photovoltaic materials, organic electronic devices, and renewable energy technologies. His publications contribute to the understanding of material performance, device optimization, and energy conversion processes that are relevant to sustainable power generation.[4]

Research Impact

Research impact is commonly evaluated through publication output, citation performance, and scholarly influence. With 154 citations and an h-index of 7, Kapil Dev Mahato’s work has received recognition from researchers working in related scientific domains. These metrics indicate that his findings have contributed to ongoing discussions and advancements within renewable energy and photovoltaic research.[1]

Award Suitability

The Best Researcher Award recognizes individuals who demonstrate sustained scholarly productivity, meaningful scientific contributions, and measurable academic impact. Kapil Dev Mahato’s research activities, publication record, citation profile, and commitment to advancing renewable energy technologies align with the objectives typically associated with research excellence awards. His work in organic solar cell research supports innovation in sustainable energy solutions and contributes to broader scientific progress.[5]

Conclusion

Kapil Dev Mahato has established a notable research presence within the field of organic solar cells through scholarly publications, citation impact, and ongoing contributions to renewable energy science. His academic achievements and dedication to advancing photovoltaic technologies support consideration for recognition through the International AI Data Scientists Award under the Best Researcher Award category.

References

  1. Elsevier. (n.d.). Scopus author details: Kapil Dev Mahato, Author ID 57886400800. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57886400800
  2. ORCID. (n.d.). Research profile of Kapil Dev Mahato.
    https://orcid.org/0000-0001-8448-2729
  3. Solar Energy Materials and Solar Cells. Organic photovoltaic technologies.
    https://doi.org/10.1016/j.solmat.2020.110585
  4. Google Scholar. (n.d.). Publication and citation profile.
    https://scholar.google.com/citations?user=yhgp8I4AAAAJ&hl=en&oi=sra
  5. International AI Data Scientists Award. Award criteria and evaluation framework.
    https://aidatascientists.com/

Abraham Marquez | Power Electronics | Best Researcher Award

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Dr. Abraham Marquez | Power Electronics | Best Researcher Award

Researcher at Universidad de Sevilla | Spain

Dr. Abraham Márquez Alcaide is a distinguished researcher in electronic engineering, renowned for his pioneering contributions to power electronics, advanced modulation strategies, and predictive control systems. Currently based at the University of Seville, he has played a vital role in the TIC-109 research group, advancing modular power converter technologies with a focus on improving system reliability, efficiency, and lifetime through smart thermal and predictive maintenance control. His prolific academic output includes over ninety peer-reviewed publications in leading high-impact journals and international conferences, several of which are recognized as highly cited by the Web of Science. Dr. Márquez has collaborated globally with eminent scholars and research institutions, including the Harbin Institute of Technology in China and Universidad Técnica Federico Santa María in Chile, fostering innovation in renewable energy integration, electric vehicle charging systems, and industrial automation. A multiple recipient of the IEEE Industrial Electronics Best Paper Award, he is widely respected for his ability to bridge theoretical advancements and industrial applications. Beyond research, he is actively engaged in academic leadership, mentoring numerous postgraduate students, organizing international conference sessions, and contributing to editorial and peer-review processes in reputed journals. His expertise spans modulation techniques, model predictive control, and active thermal management in high-reliability power electronic systems. With his visionary approach and international recognition, Dr. Márquez stands out as a leading figure shaping the future of smart, efficient, and sustainable power conversion technologies.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

Vazquez, S., Leon, J. I., Franquelo, L. G., Rodriguez, J., Young, H. A., & Marquez, A., et al. (2014). Model predictive control: A review of its applications in power electronics.

Liu, J., Vazquez, S., Wu, L., Marquez, A., Gao, H., & Franquelo, L. G. (2016). Extended state observer-based sliding-mode control for three-phase power converters.

Vazquez, S., Marquez, A., Aguilera, R., Quevedo, D., Leon, J. I., & Franquelo, L. G. (2014). Predictive optimal switching sequence direct power control for grid-connected power converters.

Liu, J., Shen, X., Alcaide, A. M., Yin, Y., Leon, J. I., Vazquez, S., Wu, L., et al. (2021). Sliding mode control of grid-connected neutral-point-clamped converters via high-gain observer.

Zhang, J., Tian, J., Alcaide, A. M., Leon, J. I., Vazquez, S., Franquelo, L. G., Luo, H., et al. (2023). Lifetime extension approach based on the Levenberg–Marquardt neural network and power routing of DC–DC converters.

Hugo Terashima Marín | Computer Science | Best Researcher Award

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Prof. Hugo Terashima Marín | Computer Science | Best Researcher Award

Professor at Tecnológico de Monterrey | Mexico

Dr. Hugo Terashima-Marín is a distinguished Professor of Computer Science and Intelligent Systems at Tecnológico de Monterrey, Mexico, widely recognized for his pioneering work in computational intelligence and heuristic optimization. His academic foundation spans prestigious institutions in Mexico, the United States, and the United Kingdom, reflecting a strong interdisciplinary background in informatics, artificial intelligence, and knowledge-based systems. As a leading researcher in evolutionary computation, constraint satisfaction problems, and hyper-heuristics, Dr. Terashima-Marín has developed innovative methodologies that bridge artificial intelligence and practical problem-solving across domains such as logistics, medicine, and smart cities. His extensive publication record in high-impact journals demonstrates his global influence in advancing algorithmic design, machine learning integration, and automated reasoning systems. Beyond research, he has mentored numerous doctoral and master’s students, fostering new generations of scientists in computational intelligence. His leadership roles at Tecnológico de Monterrey—directing graduate and doctoral programs and leading research groups in intelligent systems—underscore his commitment to academic excellence and institutional innovation. Recognized by the Mexican National System of Researchers and honored by the Mexican Academy of Sciences and the IEEE, Dr. Terashima-Marín’s contributions have elevated the standards of AI research in Latin America. His current projects explore multi-objective optimization, digital twins for smart city applications, and AI-driven decision support systems, continuing to push the boundaries of how computation can model, predict, and enhance complex human and industrial processes. Through decades of scholarship and collaboration, he remains an influential figure shaping the global discourse on intelligent systems and applied artificial intelligence.

Profiles: Scopus | ORCID

Featured Publications

Ali, F., Ahmed, A., Alipour, M. A., & Terashima-Marin, H. (2025, October 25). Adoption of AI-coding assistants in programming education: Exploring trust and learning motivation through an extended technology acceptance model.

Morales-Paredes, A., Juárez, J., Falcón-Cardona, J., Terashima-Marin, H., & Coello Coello, C. (2025, July 14). Automatic design of specialized variation operators for the multi-objective quadratic assignment problem.

Morales-Paredes, A. I., Falcón-Cardona, J. G., Juárez, J., Terashima-Marín, H., & Coello Coello, C. A. (2025, July 14). Reference point specification in greedy inclusion hypervolume-based subset selection: A study on two objectives. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2025).

Pirzado, F. A., Ahmed, A., Hussain, S., Ibarra-Vázquez, G., & Terashima-Marin, H. (2025, March 11). Assessing computational thinking in engineering and computer science students: A multi-method approach.

Garza-Santisteban, F., Cruz-Duarte, J. M., Amaya, I., Ortiz-Bayliss, J. C., Conant-Pablos, S. E., & Terashima-Marín, H. (2025, February). Selection hyper-heuristics and job shop scheduling problems: How does instance size influence performance