Peik Foong Yeap | Artificial Intelligence | Best Academic Researcher Award

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Dr. Peik Foong Yeap | Artificial Intelligence | Best Academic Researcher Award

Senior Lecturer at University of Newcastle | Singapore

Dr. Yeap Peik Foong is a distinguished academic and researcher whose career reflects a deep commitment to advancing knowledge in strategic management, organisational development, cross-cultural management, sustainability practices, and innovation within higher education and industry. Renowned for her interdisciplinary perspective, she has contributed extensively to scholarly literature through impactful journal articles, book chapters, and international conference presentations that explore themes such as digital transformation, human–AI collaboration, leadership effectiveness, consumer behaviour, knowledge management, environmental sustainability, and community-based tourism. Her work is recognized for its ability to merge theoretical frameworks with real-world applications, offering insights that guide policy development, organisational strategy, and educational leadership. She has played influential roles in shaping academic programs, strengthening research culture, and supporting curriculum innovation, while also contributing actively as a reviewer, editorial board member, and examiner for reputable journals, conferences, and institutions worldwide. Her research leadership is further demonstrated through her involvement in numerous funded projects that address emerging challenges in digital well-being, workplace resilience, global responsibility, cybersecurity, internationalisation of higher education, and interorganisational collaboration. Known for her mentorship and supervision of postgraduate candidates, she has supported research that spans management, marketing, organisational behaviour, and industry-specific strategic studies, helping shape future scholars and professionals. Her consistent engagement with global academic communities, coupled with her ability to foster collaborative networks, reflects her dedication to elevating research standards and promoting sustainable, innovative, and culturally aware practices across sectors. Dr. Yeap’s body of work positions her as a respected thought leader whose scholarly contributions and service continue to influence contemporary debates and future directions in management, education, and organisational sustainability.

Profile: Scopus

Featured Publications

Ha, H., Yeap, P. F., Loh, H. S., & Pidani, R. (2025). Environmental sustainability and CSR practices by banks in Indonesia, Malaysia, and Singapore.

Tan, K. L., Yeap, P. F., Cheong, K. C. K., & Shanu, R. (2025). Crafting an organizational strategy for the new era: A qualitative study of artificial intelligence transformation in a homegrown Singaporean hotel chain.

Tan, K.-L., Loganathan, S. R., Pidani, R. R., Yeap, P.-F., Ng, D. W. L., Chong, N. T. S., Liow, M. L. S., Cheong, K. C.-K., & Yeo, M. M. L. (2024). Embracing imperfections: A predictive analysis of factors alleviating adult leaders’ digital learning stress on Singapore’s lifelong learning journey.

Yeap, P. F., & Liow, M. L. S. (2023). Tourist walkability and sustainable community-based tourism: Conceptual framework and strategic model.

Ong, H. B., Chong, L. L., Choon, S. W., Tan, S. H., Yeap, P. F., & Kasuma, N. M. H. (2022). Retaining skilled workers through motivation: The Malaysian case.

Lee, Y. W., Dorasamy, M., Ahmad, A. A., Jambulingam, M., Yeap, P. F., & Harun, S. (2021). Synchronous online learning during movement control order in higher education institutions: A systematic review.

Bhavesh Kataria | AI and Machine Learning | AI & Machine Learning Award

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Dr. Bhavesh Kataria | AI and Machine Learning | AI & Machine Learning Award

Post-Doctoral Fellow at Emory University | United States

Dr. Bhavesh Kataria is a highly accomplished academician, researcher, and innovator in Computer Engineering, recognized globally for his leadership in Artificial Intelligence, Machine Learning, and Digital Image Processing. His professional journey spans academia and research institutions across India and the United States, including his role at Emory University, where he contributes to advanced AI-driven healthcare analytics and digital pathology solutions. With a Ph.D. focused on Optical Character Recognition of Sanskrit Manuscripts using Convolutional Neural Networks, Dr. Kataria has combined technical precision with deep domain expertise to address challenges in multilingual text recognition and medical imaging. His scholarly portfolio includes numerous publications in reputed international journals, multiple granted patents, and several authored books covering cutting-edge topics in AI, cloud computing, and web technologies. An active member of prestigious organizations such as IEEE and ACM, he serves on editorial boards of international journals and as a reviewer for globally recognized publishers like Springer Nature and Science Publishing Group. He has also chaired sessions and reviewed Ph.D. theses, contributing significantly to the academic ecosystem. Dr. Kataria’s pioneering innovations, such as AI-based network visualization tools, smart teaching devices, and healthcare monitoring systems, underscore his commitment to translational research and practical AI applications. Honored with awards including the Best Researcher Award and Teaching Excellence Award, he exemplifies a blend of scholarly excellence, innovation, and mentorship. His dedication to advancing intelligent systems and promoting interdisciplinary research continues to inspire global collaboration in emerging computational technologies.

Profiles: Scopus | ORCID

Featured Publications

Kataria, B., & Jethva, H. B. (2024, September 30). Decentralized security mechanisms for AI-driven wireless networks: Integrating blockchain and federated learning.

Kataria, B. (2024, June 2). Automated detection of tuberculosis using deep learning algorithms on chest X-rays.

Shivadekar, S., Kataria, B., Hundekari, S., Wanjale, K., Balpande, V. P., & Suryawanshi, R. (2023). Deep learning based image classification of lungs radiography for detecting COVID-19 using a deep CNN and ResNet 50.

Shivadekar, S., Kataria, B., Limkar, S., Wagh, K., Lavate, S., & Mulla, R. (2023, June 15). Design of an efficient multimodal engine for preemption and post-treatment recommendations for skin diseases via a deep learning-based hybrid bioinspired process.

Kataria, B., Jethva, H. B., Shinde, P. V., Banait, S. S., Shaikh, F., & Ajani, S. (2023, April 30). SLDEB: Design of a secure and lightweight dynamic encryption bio-inspired model for IoT networks.