Dr. Seyedeh Tina Sefati | Artificial Intelligence in Diagnostics | Best Researcher Award

Dr. Seyedeh Tina Sefati is a researcher and academic affiliated with the University of Tabriz, East Azerbaijan, Iran, where she has been serving in the Faculty of Electrical and Computer Engineering since. She is currently pursuing her PhD in Computer Engineering at the same institution, having previously earned her Master’s degree in Electronic and Computer Engineering. Her research contributions span areas of artificial intelligence, data security, federated learning, and time series analysis, with publications in internationally recognized journals. Among her key works are “Federated Reinforcement Learning with Hybrid Optimization for Secure and Reliable Data Transmission in Wireless Sensor Networks (WSNs)” , “Enhancing Autoencoder Models for Multivariate Time Series Anomaly Detection: The Role of Noise and Data Amount”, and “Improvement of Persian Spam Filtering by Game Theory” (International Journal of Advanced Computer Science and Applications. These studies demonstrate her engagement with applied machine learning, optimization techniques, and cyber reliability. Dr. Sefati’s academic profile is indexed across platforms, where her citations reflect a growing impact in computational intelligence and secure network communication. Her interdisciplinary research bridges theoretical computing and real-world technological applications, advancing intelligent systems capable of robust data analysis and anomaly detection in complex networks. With ongoing doctoral work and collaborations across multiple institutions, she continues to contribute to advancing computational methods for smart network management and artificial intelligence-based optimization. Her scholarly record, publications, and citation metrics reflect a developing research trajectory focused on next-generation AI systems and cyber-secure data transmission.