Bincy Kaluvilla | Artificial Intelligence | Best Academic Researcher Award

Dr. Bincy Kaluvilla | Artificial Intelligence | Best Academic Researcher Award

Head of Academics at Learners University College | United Arab Emirates

Dr. Bincy B. Kaluvilla is an accomplished academic leader and researcher whose work bridges the disciplines of sustainable finance, hospitality management, and real estate investment. Her professional journey reflects a deep commitment to academic excellence, innovation, and the advancement of sustainability-focused business education. As an experienced higher education professional, she has played a transformative role in shaping curricula and fostering strategic partnerships that align academic programs with contemporary industry practices. Her teaching portfolio encompasses subjects such as Real Estate Finance, Hospitality Accounting, and Corporate Finance, delivered across international undergraduate and postgraduate programs. A Fellow of the Higher Education Authority (UK) and a CPA Australia member, she brings a strong foundation in finance and accounting to her academic leadership. Her scholarly contributions span peer-reviewed journals, book chapters, and international conferences, exploring topics including ESG reporting, sustainable investment, AI integration in hospitality, and the evolving intersections of culture, ethics, and finance. Notable among her works are publications in Frontiers in Computer Science, Asia Pacific Journal of Tourism Research, Performance Measurement and Metrics, and Journal of Open Innovation. She has also contributed to edited volumes published by Springer Nature, IGI Global, Emerald, and Elsevier. Beyond research and teaching, Dr. Kaluvilla has led numerous corporate training programs for leading organizations such as the Jumeirah Group and Omran Group, promoting financial literacy and leadership within the hospitality sector. Her contributions have been recognized globally through awards and invitations to serve as visiting faculty at institutions in Malta, Japan, and China. Through her research, teaching, and leadership, she continues to champion sustainability, innovation, and excellence in global higher education and industry practice.

Profile: Google Scholar

Featured Publications

Kaluvilla, B. B., Kalarikkal, S. A., & Thamilvanan, G. (2025). AI-driven extraction and intelligent retrieval of missionary archives in Malabar: Advancing preservation and accessibility with machine learning.

Mulla, T., Kaluvilla, B. B., Zahidi, F., Alsabbah, S., & Tantry, A. (2025). “Your house looks like that show…”: Exploring consumers’ perceptions towards media-inspired home décor.

Bouchon, F., Kaluvilla, B. B., & Kolmorgon, K. (2025). Sustainable luxury hospitality: A reality beyond antagonistic terms? Innovations and trends in Maldivian luxury resorts.

Thomsen, K., Kaluvilla, B. B., & Zahidi, F. (2025). Sustainable wildlife tourism: Government guidelines and lodge contributions in Zambia.

Kaluvilla, B. B. (2025). Review of The Routledge handbook of religious and spiritual tourism, by D. H. Olsen & D. J. Timothy.

Yousef Asadi | Artificial Intelligence | Best Paper Award

Mr. Yousef Asadi | Artificial Intelligence | Best Paper Award

Master Degree at Bu Ali Sina University | Iran

Mr. Yousef Asadi is a dedicated electrical engineer and researcher whose academic and professional pursuits center on advancing power systems, smart grids, and sustainable energy technologies. With a master’s degree in electrical engineering specializing in power systems from Buali Sina University, his expertise bridges theoretical insight with practical application in energy optimization, control, and artificial intelligence. His scholarly contributions have significantly enriched the field, with impactful publications in top-tier journals such as the Journal of Energy Storage, International Journal of Electrical Power & Energy Systems, Energies, Applied Sciences, and IEEE Access. His works focus on developing intelligent frameworks for energy management, universal models for power converters, and adaptive neural control techniques for active power filters—reflecting a strong interdisciplinary command of power electronics, control theory, and computational intelligence. Asadi’s research interests span microgrid stability, distributed generation, and reinforcement learning-based optimization, positioning him at the forefront of innovation in clean and resilient energy systems. His experiences in teaching, software-hardware setup, and internships across power distribution and aviation electronics have strengthened his technical and analytical capabilities. Fluent in English, Persian, and Kurdish, he demonstrates effective communication across diverse professional environments. Known for his proficiency in MATLAB, Python, and electrical design software, he applies computational modeling and automation to solve real-world energy challenges. His continuous pursuit of advanced, sustainable solutions reflects a commitment to bridging academia and industry for the development of smarter, more efficient energy infrastructures. Through his research and technical acumen, Yousef Asadi exemplifies a new generation of engineers dedicated to transforming the global energy landscape through innovation and intelligent system design.

Profile: Scopus

Featured Publications

Mansouri, M., Eskandari, M., Asadi, Y., & Savkin, A. (2024). A cloud-fog computing framework for real-time energy management in multi-microgrid system utilizing deep reinforcement learning.

Asadi, Y., Eskandari, M., Mansouri, M., Moradi, M. H., & Savkin, A. V. (2023). A universal model for power converters of battery energy storage systems utilizing the impedance-shaping concepts.

Asadi, Y., Eskandari, M., Mansouri, M., Savkin, A. V., & Pathan, E. (2022). Frequency and voltage control techniques through inverter-interfaced distributed energy resources in microgrids

Asadi, Y., Eskandari, M., Mansouri, M., Chaharmahali, S., Moradi, M. H., & Tahriri, M. S. (2022). Adaptive neural network for a stabilizing shunt active power filter in distorted weak grids.

Mansouri, M., Eskandari, M., Asadi, Y., Siano, P., & Alhelou, H. H. (2022). Pre-perturbation operational strategy scheduling in microgrids by two-stage adjustable robust optimization.

Prof. Dr. Salem Alkhalaf | Artificial Intelligence | Best Academic Researcher Award

Prof. Dr. Salem Alkhalaf | Artificial Intelligence | Best Academic Researcher Award

Distinguished Researcher, Qassim University, Saudi Arabia

Prof. Dr. Salem Alkhalaf is a dynamic and accomplished researcher whose work spans information and communication technology, e-learning systems, and digital transformation. He holds a Ph.D. in Information and Communication Technology from Griffith University, supported by prior degrees in ICT and Computer Education. Prof. Dr. Salem Alkhalaf currently serves in senior academic and leadership roles at Qassim University, where he has steered initiatives in enterprise architecture, digital content management, and e-learning strategy. His research interests include collaborative learning environments, information quality in learning management systems, usability evaluation, and culturally adaptive educational technologies. He excels in research skills such as mixed methods design, structural equation modeling, system evaluation, cross-cultural adaptation, and large-scale empirical studies. He maintains an outstanding scholarly footprint: Scopus ID: 41661143900, with 2,021 citations across 1,885 documents, 179 published works, and an h-index of 23. His professional engagements include membership in IEEE, ACM, ACS, contributions as a reviewer and editorial board member, and leadership in national e-government and audit teams. Recognized through institutional awards, research grants, and best paper honors, he is committed to advancing scholarship, mentoring emerging researchers, and expanding global collaborations. Prof. Dr. Salem Alkhalaf combines visionary leadership with rigorous scholarship, making him a prominent figure positioned to drive future breakthroughs in AI, educational technology, and ICT research.