Synthesizing Rolling Bearing Fault Samples in New Conditions: A Framework Based on a Modified CGAN. - Maryam Ahang; Masoud Jalayer; Ardeshir Shojaeinasab; Oluwaseyi Ogunfowora; Todd Charter; Homayoun Najjaran (Sensors, 2022)

Condition Monitoring with Incomplete Data: An Integrated Variational Autoencoder and Distance Metric Framework. - Maryam Ahang; Mostafa Abbasi; Todd Charter; Homayoun Najjaran (CASE, 2024)

Intelligent Condition Monitoring of Industrial Plants: An Overview of Methodologies and Uncertainty Management Strategies. - Maryam Ahang; Todd Charter; Oluwaseyi Ogunfowora; Maziyar Khadivi; Mostafa Abbasi; Homayoun Najjaran (CoRR, 2024)

Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions. - Maziyar Khadivi; Todd Charter; Marjan Yaghoubi; Masoud Jalayer; Maryam Ahang; Ardeshir Shojaeinasab; Homayoun Najjaran (Comput. Ind. Eng., 2025)

FORLAPS: An Innovative Data-Driven Reinforcement Learning Approach for Prescriptive Process Monitoring. - Mostafa Abbasi; Maziyar Khadivi; Maryam Ahang; Patricia Lasserre; Yves Lucet; Homayoun Najjaran (CoRR, 2025)

An Innovative Next Activity Prediction Approach Using Process Entropy and DAW-Transformer. - Hadi Zare 004; Mostafa Abbasi; Maryam Ahang; Homayoun Najjaran (CoRR, 2025)

Feature-Weighted MMD-CORAL for Domain Adaptation in Power Transformer Fault Diagnosis. - Hootan Mahmoodiyan; Maryam Ahang; Mostafa Abbasi; Homayoun Najjaran (CoRR, 2025)

Multi-Channel Swin Transformer Framework for Bearing Remaining Useful Life Prediction. - Ali Mohajerzarrinkelk; Maryam Ahang; Mehran Zoravar; Mostafa Abbasi; Homayoun Najjaran (CoRR, 2025)