[5] M. Saqib, B. C. M. Fung, and P. Charland. PAC-X: Fuzzy Explainable AI for Multi-Class Malware Detection. IEEE Transactions on Fuzzy Systems, 2025.
[6] M. Saqib, S. Mahdavifar, B. C. M. Fung, and P. Charland. A comprehensive analysis of explainable AI for malware hunting. ACM Computing Surveys, 2024.
[7] M. Saqib, M. Mustaqeem, M. S. Jawed, A. Abdulaziz, A. Khan, and J. Khan. Deep-Transfer Learning inspired Natural Language Processing System for Software Requirements Classification. Knowledge and Information Systems, 2025.
[8] M. Saqib, E. Şentürk, M. A. Adil, and M. Freeshah. Seismo-ionospheric precursory detection using hybrid Bayesian-LSTM network model with uncertainty-boundaries and anomaly-intensity. Advances in Space Research, 2024.
[9] M. Sakib, S. Ahmad, K. Anwar, and M. Saqib. Optimizing Support Vector Regression using Grey Wolf Optimizer for Enhancing Energy Efficiency and Building Prototype Architecture. Cluster Computing, 2025.
[10] M. Saqib, M. A. Adil, and M. Freeshah. Pre-earthquake ionospheric perturbation analysis using deep learning techniques. Advances in Geomatics, 2023.
[11] E. Şentürk, M. Saqib, and M. A. Adil. A multi-network-based Hybrid LSTM model for ionospheric anomaly detection: A case study of the Mw 7.8 Nepal earthquake. Advances in Space Research, 2022.
[12] M. Saqib, E. Şentürk, S. A. Sahu, and M. A. Adil. Ionospheric anomalies detection using autoregressive integrated moving average (ARIMA) model as an earthquake precursor. Acta Geophysica, 2021.
[13] M. Mustaqeem and M. Saqib. Principal component-based support vector machine (PC-SVM): a hybrid technique for software defect detection. Cluster Computing, 2021.
[14] E. Şentürk, M. A. Adil, M. Saqib. Ionospheric total electron content response to annular solar eclipse on June 21, 2020. Advances in Space Research, 2021.
[15] M. Saqib, E. Şentürk, S. A. Sahu, and M. A. Adil. Comparisons of autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM) network models for ionospheric anomalies detection: a study on Haiti earthquake. Acta Geophysica, 2022.
[16] M. A. Adil, E. Şentürk, M. Shah, N. A. Naqvi, M. Saqib, and A. R. Abbasi. Atmospheric and ionospheric disturbances associated with the M > 6 earthquakes in the East Asian sector: A case study of two consecutive earthquakes in Taiwan. Journal of Asian Earth Sciences, 2021.
[17] M. Saqib. Forecasting COVID-19 outbreak progression using hybrid polynomial-Bayesian ridge regression model. Applied Intelligence, 2020.
[18] M. Saqib, M. M. Hussain, M. S. Alam, M. M. S. Beg, and A. Sawant. Smart Electric Vehicle Charging Through Cloud Monitoring and Management. Journal of Technology and Economics of Smart Grids and Sustainable Energy, 2017.
[19] M. Saqib, B. C. M. Fung, P. Charland, and A. Walenstein. H2X: Hybrid and Hierarchical Explainable Model for Malware Analysis. IEEE Transactions on Information Forensics and Security. Submitted.
[20] M. Saqib, F. Iqbal, and B. C. M. Fung. Tree-FoX: Tree-based Forensic using eXplainable AI for Malicious Memories. Digital Investigation. Submitted.
[21] M. Saqib, B. C. M. Fung, and S. H. H. Ding. MalGPT: A Generative Explainable Model for Malware Binaries. ECML PKDD, 2025.
[22] Z. Khalid, F. Iqbal, M. Saqib. Application of Unsupervised Explainable AI in Digital Forensics. DFRWS USA 2025.
[23] S. Mahdavifar, M. Saqib, B. C. M. Fung, P. Charland, and A. Walenstein. VulEXplaineR: XAI for vulnerability detection on assembly code. ECML PKDD, 2024.
[24] M. Saqib, B. C. M. Fung, P. Charland, and A. Walenstein. GAGE: genetic algorithm-based graph explainer for malware analysis. IEEE ICDE, 2024.
[25] G. Breyton, M. Saqib, B. C. M. Fung, and P. Charland. BETAC: bidirectional encoder transformer for assembly code function name recovery. IEEE DRCN, 2024.
[26] M. Saqib, S. A. Sahu and E. Şentürk. Long Short-Term Memory Network Models for Ionospheric Anomalies Detection: A Case Study for Mw7.7 Awaran, Pakistan Earthquake. IGD, 2020.
[27] M. Mustaqeem, S. Hasan, M. Saqib, and A. Talib. Cloud based disaster management and monitoring information system. IGD, 2020.
[28] M. Saqib, S. A. Sahu, M. Sakib, and E. A. Al-Ammar. Machine learning-based day-ahead market energy usage bidding for smart microgrids. In Electric Vehicle Integration in a Smart Microgrid Environment, 2021.
[29] M. Saqib, M. M. Hussain, M. S. Alam, M. M. S. Beg, and A. Sawant. Public Opinion on Viability of XEVs in India. In ISGW 2017: Compendium of Technical Papers, 2017.
[30] M. Mustaqeem, M. Saqib, M. Alam, F. Ahmad, and M. Shahid. Software Defects Prediction Using Generative Adversarial Network Based Data Balancing. In ANTIC 2024, published 2025.
[31] M. Saqib, F. Iqbal, B. C. M. Fung, and Z. Khalid. DS2TX: domain specific tree traversal eXplainable AI for malicious memory dumps. DFRWS USA, 2025.
[32] M. Saqib and B. C. M. Fung. M2X: multi-modal explainable AI for malware analysis. BDRC Cybersecurity Conference, 2024.
[33] M. Saqib. Applications of emerging technologies in Chemioinformatic. International Conference on the Emerging Trends in Chemical Sciences, 2019.
[34] C. Carr, B. Deng, S. Huayhua, K. Ibrahim, A. Jawad, F. Jung, D. Leveille, D. Napoli, A. Piché-Bustros, E. Robins, Rostamalizadeh, M. Saqib, M. Selim, D. Vanderkooi, C. Zhang, H. Assal, A. Bergeron, and I. Pustogarov. Decrypting Ransomware: Analysing and Addressing the Threat in the Canadian Context, 2023.