Bincy Kaluvilla | Artificial Intelligence | Best Academic Researcher Award

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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

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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.

Dr. Manisha Nene | Artificial Intelligence | Best Researcher Award

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Dr. Manisha Nene | Artificial Intelligence | Best Researcher Award 

Seasoned Leader, Defence Institute of Advanced Technology, India

Dr. Manisha Nene, a seasoned leader at the intersection of research, academia, and industry, holds a Ph.D. in Computer Science and has devoted over two decades to advancing artificial intelligence and cybersecurity. Throughout her career she has held key leadership roles, including Director of the School of Mathematical Sciences and Computer Engineering and Head of the Department of Computer Science & Engineering at DIAT-DRDO. Her professional experience spans guiding doctoral and master’s scholars, leading national-level research projects, and founding MAJINE Systems Pvt. Ltd., which develops cybersecurity and AI-based solutions rooted in her patented innovations. Dr. Nene’s research interests lie in secure AI, trustworthy computing, digital transformation, and responsible infrastructure. She is proficient in advanced research skills such as machine learning, adversarial defense, threat modeling, deep neural networks, cryptographic protocols, and data analytics. Over her career she has received numerous awards, including IETE’s Smt. Triveni Devi Award for her contributions to ICT for society, the Future Crime Research Foundation’s Award of Excellence for PAN-India cyber security training, institute-level Researcher of the Year awards, and multiple Best Paper Awards at international conferences. Her Scopus profile reflects 129 documents, over 716 citations, and an h-index of 13 (Scopus ID: 35488434700).

profile: GOOGLE SCHOLAR | SCOPUS | ORCID 

Featured Publications

  • Nene, M. A secure AI framework for adversarial attack mitigation in critical infrastructures. (202, 45 citations)

  • Nene, M. Trustworthy deep learning in cyber-physical systems: techniques and challenges. (2022, 55 citations)

  • Nene, M. Privacy-preserving machine learning with homomorphic encryption in cloud environments. (2020, 38 citations)

  • Nene, M. Blockchain-enabled authentication protocols for Internet of Things security. (2019, 29 citations)

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

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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.

Profile: GOOGLE SCHOLAR | SCOPUS  | ORCID

Dr. Konstantinos Kotsidis | Artificial Intelligence | Best Researcher Award

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Dr. Konstantinos Kotsidis | Artificial Intelligence | Best Researcher Award

Dr. Konstantinos Kotsidis | University of Crete | Greece

Dr. Konstantinos Kotsidis is a dedicated postdoctoral researcher whose work bridges artificial intelligence and education with a strong focus on advancing human-centered pedagogical practices. With a solid academic foundation and extensive professional experience, his contributions have consistently demonstrated a commitment to fostering creativity, critical thinking, and innovation in learning environments. He combines scholarly expertise with practical classroom application, leading to impactful educational reforms, research outputs, and international collaborations. His work continues to inspire and support both learners and educators through the responsible integration of artificial intelligence into teaching and learning.

Professional Profile

ORCID

GOOGLE SCHOLAR

Summary of Suitability

Dr. Konstantinos Kotsidis is a highly promising and impactful researcher whose work at the intersection of Artificial Intelligence and Education positions him as an outstanding candidate for the Best Researcher Award. With a PhD in Education and extensive experience in the integration of AI technologies into primary and early childhood education, he has demonstrated a unique ability to bridge theory and practice. His impressive research record—comprising 19 published books, 14 journal papers, and 7 editorial appointments—reflects both academic depth and international recognition.

Education

His academic journey reflects a clear dedication to the intersection of education and technology. He earned a PhD in Education with a specialization in the integration of artificial intelligence and educational technologies into early childhood and primary education. This advanced research was preceded by a Master’s degree in Innovative Pedagogy, where he deepened his understanding of creative teaching methodologies and modern learning frameworks. His foundation in pedagogy was first established through a Bachelor’s degree in Education, which laid the groundwork for his dual focus on teaching practice and academic research. This blend of qualifications has equipped him with the tools to transform classrooms into spaces that balance theory, research, and innovation.

Experience

Professionally, Dr. Konstantinos Kotsidis has over a decade of experience as both a teacher and teacher trainer. His classroom practice allowed him to refine methods of learner-centered instruction, while his training roles have helped over two hundred educators adopt modern technological tools in teaching. Beyond teaching, he has actively collaborated with national and international research teams to develop and implement frameworks for integrating artificial intelligence into education. His professional engagements include working with primary and early childhood education institutions on designing AI-driven teaching scenarios, as well as participating in joint projects with teacher training organizations to promote innovative, human-centered pedagogy. His combination of theoretical depth and practical application positions him as a thought leader in the application of artificial intelligence in educational contexts.

Research Interests

Dr. Konstantinos Kotsidis primary research interests are situated within human-centered artificial intelligence in education, where he investigates how intelligent systems can meaningfully support teaching and learning without diminishing the human role. Another key area of his work is teacher professional development, with a focus on building confidence and competence in applying AI applications in classrooms. He also engages deeply in research surrounding eLearning and distance learning, seeking to enhance access, personalization, and equity in digital education. Through his contributions, he envisions educational systems where technology empowers rather than replaces human creativity, making teaching more effective, adaptable, and inclusive.

Award

The scope of his contributions and innovations has earned him recognition for excellence in educational research and technology integration. His work on designing comprehensive pedagogical frameworks for human-centered AI in education, leading impactful teacher training programs, and publishing widely in peer-reviewed journals has positioned him as a distinguished candidate for research-focused awards. His achievements highlight not only scholarly significance but also measurable community impact in advancing education.

Publication Top Notes

    • The Challenges of Web 2.0 for Education in Greece: A Review of the Literature
      Year: 2013
      Citations: 25

    • The contribution of training needs assessment to teacher training: Comparative Interpretation of Results
      Year: 2010
      Citations: 11

    • Human–Centered Artificial Intelligence in Education. The critical role of the educational community and the necessity of building a holistic pedagogical framework for the use
      Year: 2024
      Citations: 8

    • Distance Teacher Training in Periods of Emergency (COVID-19 Pandemic)
      Year: 2021
      Citations: 5

    • The pedagogical use of Web 2.0 applications in teacher training, with emphasis on
      Year: 2015
      Citation5

    • Pedagogical Design and Implementation of a Distance Education Program for Teachers: The Use of Web 2.0 in the Modern School with an Emphasis on Collaboration
      Year: 2017
      Citations: 3

Conclusion

Dr. Konstantinos Kotsidis represents an outstanding example of a scholar who effectively merges research and practice to transform educational experiences. His academic achievements, professional service, and research contributions have significantly influenced both local and international educational landscapes. By developing frameworks for human-centered AI use, training hundreds of educators, and publishing widely, he has demonstrated a sustained commitment to shaping the future of education. His work is not only about integrating technology but also about ensuring that its application respects and enhances the human dimensions of teaching and learning. With his innovative vision and practical contributions, he is highly suitable for recognition through a prestigious award nomination in the field of research and education.

Tushar Kafare | Artificial Intelligence | Best Researcher Award

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Dr. Tushar Kafare | Artificial Intelligence | Best Researcher Award

Assistant Professor at Sinhgad College of Engineering, India

Dr. Tushar Vaman Kafare is an Assistant Professor in the Department of Electronics and Telecommunication (E&TC) at the Sinhgad Technical Education Society (STES). With over 14 years of experience in teaching, he has made a significant impact in the field of Electronics and Telecommunication. His research and expertise span across machine learning, deep learning, computer vision, embedded systems, and various programming languages like Python, MATLAB, C, and Embedded C. Dr. Kafare is known for his dedication to teaching and research, having guided numerous student projects and published research work, focusing particularly on machine learning applications in plant disease analysis.

Profile

Google Scholar

Education

Dr. Kafare holds an M.E. degree in Electronics and Telecommunication, as well as a B.E. in Electronics. His strong academic background has been further reinforced by his ranking 6th in his graduation. His academic qualifications, combined with extensive practical and theoretical knowledge, make him a highly skilled educator and researcher. His ongoing Ph.D. research focuses on plant disease analysis using machine learning models, showcasing his commitment to advancing technological applications in agriculture.

Experience

Having joined STES on September 7, 2022, Dr. Kafare brings with him a wealth of experience in academia and industry. His teaching career spans over 14 years, during which he has mentored undergraduate and postgraduate students. He has contributed significantly to course development and the enhancement of educational experiences for students, incorporating advanced techniques in machine learning and embedded systems. Additionally, Dr. Kafare has served as a resource person for numerous workshops and faculty development programs, further demonstrating his expertise and commitment to professional growth.

Research Interests

Dr. Kafare’s primary research interest lies in the application of machine learning and image processing for agricultural advancements. His Ph.D. research focuses on using machine learning models to analyze plant diseases, particularly in grape and apple plants, through advanced image processing techniques. He is also interested in deep learning, computer vision, and embedded systems, areas that allow for the development of innovative solutions for real-world problems. Through his research, he aims to contribute to the growing field of agri-tech by leveraging modern computational techniques to assist in plant disease diagnostics and management.

Awards

Dr. Kafare has been recognized for his outstanding contributions in teaching and research. He received the prestigious Digital Teacher Award from ICT Academy, highlighting his exceptional use of technology in education. Additionally, his academic excellence is reflected in his university ranking, securing 6th place in his graduation. In 2024, he was honored with the Best Paper Award at the International Conference on Machine Learning in Jaipur, India, acknowledging the high impact and relevance of his research in the machine learning community.

Publications

Dr. Kafare has made significant contributions to the field of machine learning and telecommunication through his publications. His work has been widely cited, demonstrating the importance of his research. Below is a list of selected publications:

Kafare, T.V. et al., “Analysis on Plant Disease Diagnosis Using Convolution Neural Networks,” International Journal of Machine Learning, 2023, Scopus/SCI.

Kafare, T.V. et al., “Segmentation Techniques for Plant Disease Detection,” Journal of Image Processing, 2022, Scopus.

Kafare, T.V., “Double Convolution in CNN for Improved Plant Disease Classification,” International Conference on Machine Learning, 2024, Conference paper.

Kafare, T.V., et al., “Fungal Disease Detection in Grapes Using Machine Learning,” Journal of Agricultural Technology, 2021, Scopus.

Conclusion

Dr. Tushar Vaman Kafare’s career is marked by his dedication to both teaching and research, with a clear focus on applying machine learning and image processing to solve practical problems in agriculture. With over 14 years of teaching experience, he has proven himself as a skilled educator and researcher. His ongoing Ph.D. research, along with his numerous publications and awards, highlights his expertise in his field. As an active participant in academic and professional activities, he continues to contribute to the development of students and the academic community at large, particularly in the domains of machine learning and embedded systems.

Balaji Dhamodharan | AI Expert | Lifetime achievement Award

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Mr Balaji Dhamodharan | AI Expert | Lifetime achievement Award

Global Data Science Leader at  NXP Semiconductors,  United States

Balaji Dhamodharan is an award-winning AI and data science visionary with over 15 years of experience driving innovation, building high-performing teams, and delivering transformative AI/ML solutions across industries such as Oil & Gas, Manufacturing, and Retail. Recognized among the Top 40 Under 40 Data Scientists and a recipient of the AI 100 Award, he excels at integrating cutting-edge technologies to optimize processes, foster business growth, and address complex challenges.

Profile:

Leadership & Impact:

  • Global Data Science Leader, NXP Semiconductors
    • Established a Center of Excellence (CoE) for Data Intelligence, delivering advanced AI solutions that saved $10M annually.
    • Led cross-functional teams to implement generative AI and machine learning strategies, achieving 30% efficiency improvements.
    • Designed and executed the Data Science Roadmap, a visionary framework for governance and innovation.
  • Technology Advisor: Consistently integrates emerging AI/ML technologies, enabling data-driven decision-making for enterprises.
  • Scaling Expertise: Built and nurtured high-performing data science teams, fostering a culture of innovation and collaboration.

Key Technical Skills:

  • AI & ML Expertise: Generative AI, LLMs, Deep Learning, MLOps, and Natural Language Processing (NLP).
  • Data Solutions: Proficient in Python, PySpark, SQL, Snowflake, and DataRobot.
  • Visualization & Cloud: Tableau, Power BI, AWS, Azure, and Databricks.

Professional Timeline:

  • NXP Semiconductors (2022 – Present): Global Data Science Leader
  • DataRobot (2021 – 2022): Lead Data Scientist
  • Yum Brands (2021): Sr. Manager, Data Science
  • Dell Technologies (2019 – 2021): Consultant, Data Science
  • Honeywell Process Solutions (2012 – 2019): Sr. Data Scientist

Accomplishments:

  • Co-inventor of a patent-pending NLP-based contract analysis algorithm.
  • Published author of the technical book “Applied Data Science using PySpark” (Apress).
  • Editorial Board Member for leading AI journals.
  • Recognized as a Global Thought Leader in Manufacturing (2024) and Generative AI Leader of the Year.
  • Forbes Technology Council Member and speaker on AI’s transformative role in digital economies.

Thought Leadership & Advocacy

  • Active contributor to advancing responsible AI practices aligned with the United Nations Sustainable Development Goals (SDGs).
  • Advisory roles at Harvard, Oklahoma State University, and Gartner’s Evanta CDAO community.
  • Advocate for ethical AI through memberships in AI 2030 Responsible AI and 3AI Leadership Council.

Publication Top Notes:

  1. Optimizing Industrial Operations: A Data-Driven Approach to Predictive Maintenance through Machine Learning
    B. Dhamodharan
    International Journal of Machine Learning for Sustainable Development, 3(1), 2021.
  2. Beyond Traditional Methods: A Novel Approach to Anomaly Detection and Classification Using AI Techniques
    B. Dhamodharan
    Transactions on Latest Trends in Artificial Intelligence, 3(3), 2022.
  3. AI-Infused Quantum Machine Learning for Enhanced Supply Chain Forecasting
    L.M. Gutta, B. Dhamodharan, P.K. Dutta, P. Whig
    Quantum Computing and Supply Chain Management: A New Era of Optimization, 48–63, 2024.
  4. Empowering Enterprise Intelligence: The Transformative Influence of AutoML and Feature Engineering
    B. Dhamodharan
    International Journal of Creative Research in Computer Technology and Design, 2023.
  5. Driving Business Value with AI: A Framework for MLOps-Driven Enterprise Adoption
    B. Dhamodharan
    International Journal of Sustainable Development in Computing Science, 5(4), 2023.
  6. Harnessing Disaster Tweets: A Deep Dive into Disaster Tweets with EDA, Cleaning, and BERT-Based NLP
    B. Dhamodharan
    International Transactions in Artificial Intelligence, 6(6), 1–14, 2022.
  7. Applied Data Science Using PySpark: Learn the End-to-End Predictive Model-Building Cycle
    R. Kakarla, S. Krishnan, V. Gunnu, B. Dhamodharan
    Apress, 2024.
  8. Quantum Computing Applications in Real-Time Route Optimization for Supply Chains
    R.K. Vaddy, B. Dhamodharan, A. Jain
    Quantum Computing and Supply Chain Management: A New Era of Optimization, 2024.
  9. Multilingual Tokenization Efficiency in Large Language Models: A Study on Indian Languages
    B.D. Mohamed Azharudeen M
    Lattice – The Machine Learning Journal, 5(2), 2024.