Ms. Shanazeer C K | Deep Learning | Best Researcher Award

Ms. Shanazeer C K | Deep Learning | Best Researcher Award

Ms. Shanazeer C K | Pondicherry University Karaikal Campus | India

Dr. Shahnazeer C K is an accomplished academic and dedicated researcher in the field of Computer Science and Engineering, currently pursuing her research as a scholar at Pondicherry University, Karaikal Campus. With a strong academic foundation and an innovative research mindset, she has made significant contributions to computational intelligence and cloud computing, particularly focusing on developing frameworks that integrate artificial intelligence, deep learning, and federated learning for solving complex real-world problems. She combines her expertise in machine learning, data analytics, and cloud-based systems to create solutions that are not only technically advanced but also socially impactful. Her dedication to continuous learning and research excellence has established her as a promising researcher with a clear vision to contribute to advancements in computational technologies and intelligent systems.

Professional Profile

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SCOPUS

Summary of Suitability

Dr. Shahnazeer C K is an accomplished researcher and scholar in the field of Computer Science and Engineering, specializing in Computational Intelligence, Machine Learning, and Cloud Computing. With  combined academic and industry experience, she has made significant contributions through impactful research, innovative frameworks, and technology-driven solutions, positioning her as a strong candidate for the Best Researcher Award.

Education

Dr. Shahnazeer C K holds a Bachelor of Technology (B.Tech.) in Information Technology from the Government Engineering College, Sreekrishnapuram, Kerala, which laid a strong foundation in computer science fundamentals and system design. She further enhanced her academic expertise by completing her Master of Technology (M.Tech.) in Information Technology from Anna University, Coimbatore, Tamil Nadu. Her postgraduate studies allowed her to specialize in advanced computing techniques, algorithms, and intelligent systems, equipping her with the technical and analytical skills essential for solving modern computational challenges. Currently, she is pursuing a Doctor of Philosophy (Ph.D.) in Computer Science and Engineering at Pondicherry University, Karaikal Campus, where her research work primarily focuses on computational intelligence and its applications in multi-disease prediction and federated learning frameworks.

Experience

With over nine years of academic experience as an Assistant Professor in various engineering colleges across Kerala, Dr. Shahnazeer C K has consistently demonstrated her ability to impart quality education, mentor students, and contribute to curriculum development in computer science-related disciplines. In addition to her academic expertise, she has four years of industry experience, which provided her with practical exposure to real-time problem-solving, software development, and system integration. Her combined academic and industry background has enabled her to bridge the gap between theoretical concepts and practical implementations, making her a versatile and resourceful professional in the field of computer science. Her active involvement in teaching, research, and guiding students has positioned her as a key contributor to academic and research excellence.

Research Interests

Dr. Shahnazeer C K core research interests lie in Computational Intelligence, Cloud Computing, Machine Learning, and Federated Learning. Her ongoing research focuses on designing intelligent frameworks that leverage deep learning, transfer learning, and federated learning techniques to improve multi-disease prediction models while maintaining patient data privacy and security. One of her key contributions includes the development of a Federated Transfer Learning (FTL) Framework designed to predict multiple diseases such as heart, kidney, lung, and liver conditions using clinical and laboratory datasets. The framework integrates preprocessing techniques like normalization, feature selection, and imputation with advanced machine learning classifiers such as Support Vector Machines (SVM), delivering improved accuracy, robustness, and reliability. Her research is further enhanced by cloud-based deployments using Amazon Web Services (AWS), ensuring scalability and efficient data processing. Through her work, she aims to advance intelligent healthcare solutions by combining innovative computational methods with real-world applications.

Awards

Dr. Shahnazeer C K has authored four books with ISBN numbers, showcasing her expertise in emerging areas of computer science and engineering. She has also successfully filed two patents and has one patent under process, demonstrating her commitment to technological innovation and the development of novel computational solutions. As an active member of professional organizations such as the IEEE Computational Intelligence Society, IEEE Computer Society, IEEE Electron Devices Society, and IEEE Young Professionals, she stays engaged with the latest trends and contributes to the advancement of the research community. Her professional memberships enable her to collaborate with peers, exchange knowledge, and remain at the forefront of cutting-edge technologies. These achievements reflect her consistent efforts toward research excellence, innovation, and impactful contributions to society.

Publication Top Notes

Digital Misinformation and Fake News Detection using WoT Integration with Asian Social Networks Fusion-based Feature Extraction with Text and Image Classification by Machine
Year: 2022
Citations: 9

A TDMA-Based Smart Clustering Technique for VANETs
Year: 2014
Citations: 7

Efficient Multipath Routing Protocol for VANET using Path Restoration
Year: 2013
Citations: 6

6G Cyber Physical System-based Smart Healthcare Modelling by Mobile Edge Network and Artificial Intelligence
Year: 2024
Citations: 3

Increasing the Lifetime of Cluster Head using Improved Stability-based Clustering Approach in VANETs
Year: 2015
Citations: 1

Conclusion

Through her consistent research efforts, academic contributions, and innovations, Dr. Shahnazeer C K has established herself as an emerging leader in computational intelligence and cloud-based intelligent systems. Her ongoing work demonstrates a unique combination of technical expertise, practical applications, and social impact, particularly in the domain of multi-disease prediction frameworks and privacy-preserving healthcare analytics. With her growing portfolio of publications, patents, and books, she continues to contribute significantly to the scientific community and inspire future researchers. Her dedication to advancing computational intelligence makes her a highly deserving candidate for the Best Researcher Award, highlighting her commitment to excellence, innovation, and meaningful contributions to the field of computer science and engineering.

Jamal Raiyn | Deep Learning | Best Researcher Award

Prof. Dr. Jamal Raiyn | Deep Learning | Best Researcher Award

Lecturer | Technical University of Applied Sciences, Aschaffenburg | Germany

Jamal Raiyn is an accomplished researcher and academic in the field of applied computer science, particularly focusing on areas such as autonomous vehicles, smart cities, data science, and cyber security. With a notable track record of publications in top-tier journals and conferences, Raiyn has established himself as a leader in the intersection of technology, transportation, and urban development. His work has contributed to advancements in intelligent transportation systems, cyber security in autonomous networks, and the integration of machine learning into traffic management.

Profile

Google Scholar

Education

Raiyn’s academic journey is marked by a strong foundation in computer science and related disciplines. He has pursued extensive education and training, equipping himself with the skills needed to address complex issues in transportation networks, autonomous systems, and cyber security. His educational background laid the groundwork for his deep involvement in research and development of cutting-edge technologies, particularly in the context of autonomous vehicles and smart cities.

Experience

Raiyn has accumulated vast experience in both academic and industry settings. Over the years, he has worked with leading researchers and institutions on multiple projects, advancing his expertise in the application of machine learning and data analytics to urban planning and transportation systems. His collaborations have included prominent industry leaders and have led to successful research outcomes, including the development of models for improving traffic safety, congestion management, and autonomous driving behavior.

Research Interests

Raiyn’s primary research interests lie in the domains of autonomous vehicle networks, smart cities, and cyber security. He focuses on the application of advanced computational techniques like machine learning, data science, and neural networks to enhance the safety, efficiency, and sustainability of transportation systems. Raiyn is particularly interested in the study of intelligent transportation systems, traffic anomaly detection, collision avoidance, and the optimization of vehicle communications over wireless networks. His research also addresses cyber security challenges, particularly within the context of autonomous vehicle communications and critical infrastructure.

Awards

Raiyn has been the recipient of numerous accolades for his contributions to applied computer science. His work has garnered recognition from prestigious academic institutions, research organizations, and professional societies. Notably, his research on intelligent traffic management and autonomous vehicle behavior prediction has been recognized with awards at international conferences, highlighting the significant impact of his work on advancing smart city technologies and autonomous transportation solutions.

Publications

Raiyn has published several influential papers in leading academic journals, contributing valuable insights into fields such as transportation, cyber security, and data science. Some of his notable publications include:

Raiyn, J., & Weidl, G. (2025). “Improvement of Collision Avoidance in Cut-In Maneuvers Using Time-to-Collision Metrics.” Smart Cities.

Raiyn, J., Chaar, M. M., & Weidl, G. (2025). “Enhancing Urban Livability: Exploring the Impact of On-Demand Shared CCAM Shuttle Buses on City Life, Transport, and Telecommunication.”

Raiyn, J., & Weidl, G. (2024). “Predicting Autonomous Driving Behavior through Human Factor Considerations in Safety-Critical Events.” Smart Cities, 7(1), 460-474.

Raiyn, J. (2024). “Maritime Cyber-Attacks Detection Based on a Convolutional Neural Network.” Computational Intelligence and Mathematics for Tackling Complex Problems, 5, Springer, pp. 115-122.

Raiyn, J., & Rayan, A. (2023). “Identifying Safety-Critical Events in Data from Naturalistic Driving Studies.” International Journal of Simulation Systems, Science & Technology, 24(1).

Raiyn, J. (2022). “Detection of Road Traffic Anomalies Based on Computational Data Science.” Discover Internet of Things, 2(6).

Raiyn, J. (2022). “Using Dynamic Market-Based Control for Real-Time Intelligent Speed Adaptation Road Networks.” Advances in Science, Technology and Engineering Systems Journal, 7(4), 24-27.

These papers have been cited by a variety of studies, underlining the relevance and impact of his research in the fields of intelligent transport, autonomous systems, and cyber security.

Conclusion

Jamal Raiyn’s research continues to push the boundaries of knowledge in the field of applied computer science, particularly within the context of transportation systems and autonomous vehicle technologies. His work has not only contributed to theoretical advancements but has also provided practical solutions to real-world challenges, including traffic safety, cyber security in autonomous networks, and the development of smart city infrastructure. Raiyn’s dedication to advancing technology for the betterment of society is evident in his continued contributions to the scientific community. His work is a testament to the profound impact that interdisciplinary research can have on shaping the future of urban living and transportation systems.