Abrar Alanzi | Pediatric Dentistry | Best Researcher Award

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Assoc. Prof. Dr. Abrar Alanzi | Pediatric Dentistry | Best Researcher Award

Associate Professor | Kuwait University | Kuwait

Assoc. Prof. Dr. Abrar Alanzi is an Associate Professor and Consultant Pediatric Dentist at Kuwait University’s College of Dentistry. Her research and professional expertise center on pediatric oral health, preventive dentistry, and behavioral aspects influencing children’s dental outcomes. She has made significant scholarly contributions through studies on oral health-related quality of life, dental caries, molar-incisor hypomineralization, and the impact of lifestyle factors such as media use and nutrition on pediatric oral health. Her publications appear in leading international journals, reflecting a strong focus on evidence-based approaches to improving oral health in children. Beyond research, Dr. Alanzi has extensive teaching and mentorship experience, guiding undergraduate and postgraduate dental students in clinical and didactic courses. She has also contributed to academic leadership as Acting Chair of the Department of Developmental and Preventive Sciences and Director of the Community Service Unit, promoting oral health education and outreach programs in schools and underserved communities. Her dedication extends to global humanitarian efforts, leading pediatric dental missions across Africa and Asia to provide free dental care for children in need. Dr. Alanzi’s work integrates research, education, and community engagement, positioning her as a recognized figure in pediatric dentistry with a commitment to advancing oral health standards both locally and internationally.

Profiles: Scopus | Google Scholar

Featured Publications

Alanzi, A., Honkala, S., Honkala, E., Varghese, A., Tolvanen, M., & Söderling, E. (2018). Effect of Lactobacillus rhamnosus and Bifidobacterium lactis on gingival health, dental plaque, and periodontopathogens in adolescents: A randomized placebo-controlled clinical trial. Beneficial Microbes, 9(4), 593–602.

Alanzi, A., Faridoun, A., Kavvadia, K., & Ghanim, A. (2018). Dentists’ perception, knowledge, and clinical management of molar–incisor hypomineralisation in Kuwait: A cross-sectional study. BMC Oral Health, 18(1), 34.

Alanzi, A., Husain, F., Husain, H., Hanif, A., & Baskaradoss, J. K. (2023). Does the severity of untreated dental caries of preschool children influence the oral health-related quality of life? BMC Oral Health, 23(1), 552.

Alanzi, A., Minah, G., Romberg, E., Catalanotto, F., Bartoshuk, L., & Tinanoff, N. (2013). Mothers’ taste perceptions and their preschool children’s dental caries experiences. Pediatric Dentistry, 35(7), 510–514.

Alanzi, A., Söderling, E., Varghese, A., & Honkala, E. (2016). Xylitol chewing gums on the market: Do they prevent caries? Oral Health & Preventive Dentistry, 14(5), 459–466.

Benitha Christinal J | Computer Science | Women Researcher Award

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Mrs. Benitha Christinal J | Computer Science | Women Researcher Award

Assistant Professor | Presidency University | India

Mrs. Benitha Christinal J is an accomplished academic and researcher specializing in Computer Science and Engineering with a strong focus on Artificial Intelligence, Deep Learning, and Internet of Things (IoT). She has extensive professional experience in higher education, demonstrating excellence in teaching, curriculum development, and academic coordination. Her research interests include deep learning applications for cybersecurity, decentralized systems, and intelligent data analysis. She has published numerous papers in reputed international journals such as Oxidation Communications, Ain Shams Engineering Journal, Journal of Supercomputing, and Optical Fiber Technology, addressing challenges in areas like federated learning, SDN-IoT security frameworks, and evolutionary intrusion detection systems. She has also presented her work at several international conferences, contributing to advancements in AI-based healthcare, blockchain-enabled sustainability, and smart network optimization. A published author of a textbook on Database Management Systems, she has guided multiple undergraduate and postgraduate projects that have gained recognition at academic and professional levels. Her technical proficiency spans programming languages like Python, Java, and C++, and tools for web and data driven applications. Beyond research and teaching, she has been actively involved in organizing academic events, fostering industry collaborations, and mentoring students toward innovation. Her commitment to advancing technology education and research underscores her vision of shaping the next generation of computer science professionals through excellence, creativity, and applied intelligence.

Profiles: Scopus | Orcid

Featured Publications

Benitha Christinal, J., Betsee Natasha, A., Nivethitha, M., Asmitha, E., & Kaviya, N. (2025). A modern generative AI framework for Alzheimer detection leveraging autoencoders and softmax classifier. In Proceedings of the 3rd International Conference on Augmented Intelligence and Sustainable Systems (ICAISS 2025). IEEE.

Benitha Christinal, J., Jagadeesh, S., Ajai, M., Lakshman, A., & Betsee Natasha, A. (2025). Memory Montage: Amnesia support appa. In Proceedings of the International Conference on Emerging Trends in Engineering and Technology (ICETET 2025). IEEE.

Benitha Christinal, J., & Ameelia Roseline, A. (2025, September). Securing SDON with hybrid evolutionary intrusion detection system: An ensemble algorithm for feature selection and classification. Optical Fiber Technology, 104206.

Benitha Christinal, J., Chandran, V., Srinic, J., & Prasannasrinivasan, A. (2024). A distributed node clustering coalition game for mobile ad hoc networks. In Proceedings of the Asia Pacific Conference on Innovation in Technology (APCIT 2024). IEEE.

Sumanth, V., Anitha, K., Christinal, J. B., Sekhar, G. S., Khekare, G., Patil, H., Kumar, N. M., & Rajaram, A. (2024). Advanced communications and networking for environmental protection monitoring in remote wilderness areas. Journal of Environmental Protection and Ecology, 25(3), 1012–1023.

Pratap Chandra Mandal | Operations | Best Researcher Award

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Dr. Pratap Chandra Mandal | Operations | Best Researcher Award

Assistant Professor | Indian Institute of Management Shillong | India

Dr. Pratap Chandra Mandal is an Assistant Professor of Marketing at the Indian Institute of Management Shillong, recognized for his extensive academic and research experience in marketing, consumer behavior, and service management. His research primarily focuses on customer satisfaction, service quality, and consumer decision making processes, with a strong emphasis on developing reliable and validated measurement scales to assess satisfaction in diverse service contexts such as retail banking and service recovery. His doctoral research contributed significantly to understanding the multidimensional nature of customer satisfaction in the Indian retail banking sector through the integration of qualitative and quantitative methodologies, including grounded theory, factor analysis, and structural equation modeling. Over the course of his academic career, he has demonstrated a sustained commitment to high quality scholarship, publishing in peer reviewed journals and serving as a dedicated peer reviewer for reputed international journals such as the Journal of Global Marketing and Cogent Food and Agriculture. He has been consistently recognized for his academic excellence, research contributions, and professional engagement in advancing marketing education and research. His teaching and research interests encompass areas such as consumer psychology, marketing analytics, strategic marketing, and service innovation, through which he continues to contribute to the development of evidence based insights and the cultivation of future marketing professionals.

Profiles: Scopus | Google Scholar

Featured Publications

Mandal, P. C., Mukherjee, I., Paul, G., & Chatterji, B. N. (2022). Digital image steganography: A literature survey. Information Sciences, 609, 1451–1488.

Mandal, P. C. (2018). Qualitative research: Criteria of evaluation. Qualitative Research, 3(2), 1–6.

Mandal, P. C. (2012). Evaluation of performance of the symmetric key algorithms: DES, 3DES, AES and Blowfish. Journal of Global Research in Computer Science, 3(8), 67–70.

Mandal, P. C. (2014). Net promoter score: A conceptual analysis. International Journal of Management Concepts and Philosophy, 8(4), 209–219.

Mandal, P. C., Mukherjee, I., & Chatterji, B. N. (2021). High capacity reversible and secured data hiding in images using interpolation and difference expansion technique. Multimedia Tools and Applications, 80(3), 3623–3644.

Jun Tang | Computer Science | Best Researcher Award

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Mr. Jun Tang | Computer Science | Best Researcher Award

AI Algorithm Researcher | Chengdu Zhihui Heneng City Technology | China

Mr. Jun Tang is a researcher specializing in intelligent transportation and autonomous driving, with a strong focus on the integration of computer vision and artificial intelligence to enhance vehicular perception and decision making systems. His research primarily explores large vision foundation models and their applications in object detection, scene understanding, and adaptive driving environments. He has contributed to developing advanced detection frameworks that leverage reinforcement learning to improve recognition accuracy, robustness, and real time responsiveness in dynamic traffic conditions. Mr. Tang’s recent interests include prompt-guided object detection methods that utilize natural language and contextual cues to refine visual understanding within autonomous systems. Through his work at Chengdu Zhihui Heneng City Technology, he plays a key role in bridging the gap between theoretical AI models and practical intelligent mobility applications, fostering innovations that advance the safety, efficiency, and scalability of next generation transportation systems. His interdisciplinary approach combines deep learning, machine perception, and cognitive automation, contributing to the development of more adaptive and human like decision making in autonomous vehicles.

Profile: Orcid

Featured Publications

Tang, J., Li, D., Yang, J., Chen, J., & Yuan, R. (2025). Leveraging large visual models for enhanced object detection: An improved SAM-YOLOv5 model. Knowledge-Based Systems, 114757.

Tang, J. (2025, August 29). RT-DETR-based intelligent transportation object detection optimization method and system with prompt mechanism fusion.

Tang, J. (2025, May 27). Object detection method and system based on prompt engineering and regional text description.

Tang, J. (2025, April 11). Quantitative evaluation method and system for multimodal large models.

Tang, J. (2025, January 17). Evaluation method and system for urban governance multimodal large models based on text labeling.