A Comparison of TCN and LSTM Models in Detecting Anomalies in Time Series Data. - Saroj Gopali; Faranak Abri; Sima Siami-Namini; Akbar Siami Namin (IEEE BigData, 2021)

A Comparative Study of Detecting Anomalies in Time Series Data Using LSTM and TCN Models. - Saroj Gopali; Faranak Abri; Sima Siami-Namini; Akbar Siami Namin (CoRR, 2021)

Vulnerability Detection in Smart Contracts Using Deep Learning. - Saroj Gopali; Zulfiqar Ali Khan; Bipin Chhetri; Bimal Karki; Akbar Siami Namin (COMPSAC, 2022)

A Survey on Blockchain-Based Federated Learning and Data Privacy. - Bipin Chhetri; Saroj Gopali; Rukayat Olapojoye; Samin Dehbashi; Akbar Siami Namin (COMPSAC, 2023)

The Performance of Sequential Deep Learning Models in Detecting Phishing Websites Using Contextual Features of URLs. - Saroj Gopali; Akbar Siami Namin; Faranak Abri; Keith S. Jones (SAC, 2024)

The Applicability of LLMs in Generating Textual Samples for Analysis of Imbalanced Datasets. - Saroj Gopali; Faranak Abri; Akbar Siami Namin; Keith S. Jones (IEEE Access, 2024)

A Comparative Multivariate Analysis of VAR and Deep Learning-Based Models for Forecasting Volatile Time Series Data. - Saroj Gopali; Sima Siami-Namini; Faranak Abri; Akbar Siami Namin (IEEE Access, 2024)

The performance of the LSTM-based code generated by Large Language Models (LLMs) in forecasting time series data. - Saroj Gopali; Sima Siami-Namini; Faranak Abri; Akbar Siami Namin (Nat. Lang. Process. J., 2024)

IoT Malware Network Traffic Detection using Deep Learning and GraphSAGE Models. - Nikesh Prajapati; Bimal Karki; Saroj Gopali; Akbar Siami Namin (CoRR, 2025)