Sayed Abdul Majid Gilani | Emerging Technologies | Best Researcher Award

Dr. Sayed Abdul Majid Gilani | Emerging Technologies | Best Researcher Award

Dr. Sayed Abdul Majid Gilani | Birmingham City University | United Kingdom

Dr. Sayed Abdul Majid Gilani is an accomplished researcher in electrical and electronic engineering, specializing in embedded systems, automation, and control engineering. His multidisciplinary research integrates hardware design, sensor networks, and artificial intelligence to develop innovative and energy-efficient solutions for real-world challenges. With over a decade of experience in academia and applied research, Dr. Gilani has contributed significantly to the advancement of embedded control technologies, renewable energy optimization, and industrial automation systems. His work emphasizes intelligent system design, IoT-based automation, and the integration of machine learning algorithms for enhanced performance and sustainability. Dr. Gilani has published extensively in high-impact journals and presented at leading international conferences, reflecting his global engagement and scientific rigor. He has also supervised numerous research projects and guided students in developing practical applications of emerging technologies. His research outputs demonstrate a strong commitment to technological innovation that bridges the gap between theory and application. Recognized for his academic excellence and collaborative research initiatives, Dr. Gilani continues to advance cutting-edge developments that contribute to the evolution of smart, adaptive, and efficient engineering systems—making him a deserving candidate for the Best Researcher Award.

Profiles: Google Scholar | Scopus | LinkedIn | Research Gate

Featured Publications 

Gilani, S. A. M., & Faccia, A. (2021). Broadband connectivity, government policies, and open innovation: The crucial IT infrastructure contribution in Scotland. Journal of Open Innovation: Technology, Market, and Complexity, 8(1), 1. https://doi.org/10.3390/joitmc8010001

Gilani, S. A. M., Copiaco, A., Gernal, L., Yasin, N., Nair, G., & Anwar, I. (2023). Savior or distraction for survival: Examining the applicability of machine learning for rural family farms in the United Arab Emirates. Sustainability, 15(4), 3720. https://doi.org/10.3390/su15043720

Gilani, S., Gernal, L., Tantry, A., Yasin, N., & Sergio, R. (2022). Leadership styles adopted by Scottish micro-businesses during the COVID-19 pandemic. In Proceedings of the International Conference on Business and Technology (pp. 144–156). Springer.

Al Jaghoub, J., Suleiman, A., Takshe, A. A., Moussa, S., Gilani, S. A. M., Sheikh, S., & others. (2024). The role of innovation in waste management for enterprises: A critical review of the worldwide literature. In Technology-Driven Business Innovation (pp. 453–464). Springer.

Gernal, L., Tantry, A., Gilani, S. A. M., & Peel, R. (2024). The impact of online learning and soft skills on college student satisfaction and course feedback. In Technology-Driven Business Innovation: Unleashing the Digital Advantage (pp. 42–54). Springer.

Gilani, S. A. M., Tantry, A., Askri, S., Gernal, L., & Sergio, R. (2023). Adoption of machine learning by rural farms: A systematic review. In Proceedings of the International Conference on Computing and Informatics (pp. 324–335). Springer.

Mr. Ehsan Esmaeeli | Research Excellence | Best Researcher Award | 2537

Mr. Ehsan Esmaeeli | Research Excellence | Best Researcher Award

Mr. Ehsan Esmaeeli | Sharif University of Technology | Iran

Ehsan Esmaeeli, a dedicated researcher in Maintenance and Reliability Engineering at Sharif University of Technology, exemplifies excellence in research, innovation, and professional expertise. His scholarly contributions span maintenance optimization, reliability modeling, and intelligent asset management systems, integrating AI and hybrid optimization techniques. With multiple publications in high-impact international journals such as IEEE Access and Journal of Quality in Maintenance Engineering, his work has advanced the understanding of data-driven maintenance strategies and sustainable industrial operations. A Certified Maintenance and Reliability Professional (CMRP), Asset Management Assessor (CAMA), and Reliability Leader (CRL), Ehsan bridges academic research with industrial practice, fostering innovation that enhances system reliability and operational efficiency.

Profile: ScopusOrcid

Featured Publications

Esmaeeli, E., Collins, A. J., Varmazyar, M., & Khorshidnia, M. (2025). Agent-based modeling applications in maintenance systems: A systematic review. Journal of Quality in Maintenance Engineering, 31(3), 325–349. https://doi.org/10.1108/JQME-03-2024-0028

Ajit Yadav | Research Excellence | Best Researcher Award

Mr. Ajit Yadav | Research Excellence | Best Researcher Award

Mr. Ajit Yadav | Indian Institute of Technology Indore | India

Mr. Ajit Yadav is a Ph.D. Scholar in Electrical Engineering at the Indian Institute of Technology (IIT) Indore, specializing in two-dimensional transition metal dichalcogenide (2D-TMD)-based IoT-enabled biosensors for early disease detection. His research integrates nanomaterials synthesis via chemical vapor deposition (CVD) with smart sensor technology, enabling real-time and highly sensitive biomolecule detection. He has two granted patents on point-of-care diagnostic systems and toxic gas detection technologies and has published three peer-reviewed papers in leading SCI-indexed journals such as the IEEE Sensors Journal and Journal of Electroanalytical Chemistry. His collaborative projects with AIIMS Bhopal and RMIT University, Australia, strengthen the biomedical application and global impact of his work. Through innovative sensor design, IoT integration, and interdisciplinary collaboration, Mr. Yadav’s research contributes to the advancement of portable, scalable, and intelligent biosensing platforms, supporting the future of personalized healthcare and environmental monitoring.

Profile: OrcidGoogle Scholar

Featured Publications

Verma, V. K., Patel, C., Chaudhary, S., Yadav, A., Bajoria, P., Ako, R. T., Sriram, S., & Mukherjee, S. (2025). Pd-loaded MoS₂ nanoflowers for enhanced room-temperature methanol sensing. IEEE Sensors Journal, 25(2), 2186–2193. https://doi.org/10.1109/JSEN.2024.3506014

Yadav, A., Patel, C., Kanwar, J. R., Sriram, S., & Mukherjee, S. (2025). Miniaturized IoT-enabled MoS₂-based electrochemical sensor for real-time adenine monitoring. Journal of Electroanalytical Chemistry, 119564. https://doi.org/10.1016/j.jelechem.2025.119564

Yadav, A., Patel, C., Verma, V. K., Kanwar, J. R., Sriram, S., & Mukherjee, S. (2025). A point-of-care and IoT-enabled MoS₂-based sensor for uric acid detection in human serum. IEEE Sensors Journal, 25(20), 37714–37721. https://doi.org/10.1109/JSEN.2025.3609535