EV-Integrated Power System Transient Stability Prediction Based on Imaging Time Series and Deep Neural Network. - Tohid Behdadnia; Mehmet Parlak (ITSC, 2021)

Mitigating Erroneous PMU measurements via an ANN to Enhance ML-based Transient Stability Prediction Accuracy. - Tohid Behdadnia; Mehmet Parlak (IEEE DataPort, 2021)

A New Deep Learning-Based Strategy for Launching Timely DoS Attacks in PMU-Based Cyber-Physical Power Systems. - Tohid Behdadnia; Geert Deconinck (ISGT-Europe, 2022)

Anomaly Detection in Automatic Generation Control Systems Based on Traffic Pattern Analysis and Deep Transfer Learning. - Tohid Behdadnia; Geert Deconinck (CoRR, 2022)

Encrypted Traffic Classification for Early-Stage Anomaly Detection in Power Grid Communication Network. - Tohid Behdadnia; Geert Deconinck; Can Özkan; Dave Singelée (ISGT EUROPE, 2023)

Spatial-Temporal Graph Neural Network for Detecting and Localizing Anomalies in PMU Networks. - Tohid Behdadnia; Klaas Thoelen; Fairouz Zobiri; Geert Deconinck (EDCC Workshops, 2024)

Leveraging Deep Learning to Increase the Success Rate of DoS Attacks in PMU-Based Automatic Generation Control Systems. - Tohid Behdadnia; Klaas Thoelen; Fairouz Zobiri; Geert Deconinck (IEEE Trans. Ind. Informatics, 2024)

Early-Stage Anomaly Detection in IT-OT Power Grid Communication Networks Using Wavelet Transform and Hybrid Deep Learning. - Tohid Behdadnia; Klaas Thoelen; Geert Deconinck (IEEE Trans. Smart Grid, 2025)