Rate My Professor Seyedamin Pouriyeh

Pouriyeh has authored numerous peer-reviewed publications in leading journals and conferences. Key works include 'Federated-Learning-Based Anomaly Detection for IoT Security Attacks' (2021), 'A Survey on Security and Privacy of Federated Learning' (2020), 'Secure Smart Communication Efficiency in Federated Learning: Achievements and Challenges' (2022), 'A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques' (2017), and 'Ontology Summarization: Graph-Based Methods and Beyond' (2019). More recent publications feature 'AI-Guided Binding Mechanisms and Molecular Dynamics for MERS-CoV' (2026), 'Enhancing Alzheimer’s Diagnosis Through Spontaneous Speech Recognition: Deep Learning Approach with Data Augmentation' (2025), and 'Privacy-Preserving Federated Learning-Based Intrusion Detection System for IoHT Devices' (2024). At Kennesaw State University, he teaches courses such as IT4883 and actively engages students through his research lab, focusing on machine learning and cybersecurity projects. His expertise spans blockchain for secure systems, deep learning in protein structure prediction, and anomaly detection in smart healthcare.