Biography

Dr. Mona Nashaat is an academic staff member at Port Said University, Egypt. She specializes in artificial intelligence, data analytics, and intelligent systems, with a strong focus on applying advanced computational techniques to real-world problems.

Her academic and research interests include machine learning, intelligent decision-support systems, data analysis, and the development of AI-based applications in various domains. She has authored and co-authored several research papers published in international journals and conference proceedings.

In addition to her research activities, Dr. Nashaat is actively involved in teaching undergraduate and postgraduate courses related to artificial intelligence, programming, data analysis, and software systems. She also contributes to curriculum development, digital transformation initiatives, and academic quality assurance within the university.

Dr. Nashaat is engaged in interdisciplinary projects that bridge academic research with practical applications, aiming to support innovation, entrepreneurship, and sustainable development in higher education.

Educational Qualification

• Department of Electrical and Computer Engineering- University of Alberta             2016-2020

Doctor of Philosophy in Software Engineering and Intelligent Systems

Thesis Title: Developing and Evaluating Algorithms for Fixing Omission and Commission Errors in Structured Data.

• Faculty of Engineering - Port Said University                                                                   2011-2014

Master’s degree in electrical engineering, Computer and Control Division. 

Thesis Title: Static Code Analysis for Enhancing Web Applications Using Program Transformation Tools.

• Faculty of Engineering - Suez Canal University                                                                2003-2008

B.Sc. Degree in Electrical Engineering, Computer Engineering, and Automatic Control Division.

Overall Grade: Very Good With an Honors Degree.     Graduation Project Grade: Excellent.

Academic And Professional Experience

• Assistant Professor                                                                                           2020-Present
• Teached Courses:

Electrical Engineering Department – Faculty of Engineering - Port Said University

• Assistant Professor (Part-time)                                                                     2024-Present

Faculty of Engineering – Arab Academy for Science, Technology & Maritime Transport

• Assistant Professor (Part-time)                                                                     2024-Present

Faculty of Computer Science – Misr International University (MIU)

• Assistant Professor (Part-time)                                                                     2021-2025

Faculty of Engineering – East Port Said National University

• Assistant Professor (Part-time)                                                                     2021-Present

Faculty of Industry and Energy – East Port Said University of Technology

• Postdoctoral Fellow                                                                                          June 2023-Dec. 2023

Department of Electrical and Computer Engineering – Faculty of Engineering – University of Alberta

• Graduate Research and Assistant Fellow                                                    Jan. 2017 to August 2020

Department of Electrical and Computer Engineering – Faculty of Engineering – University of Alberta

• Principal Instructor | University of Alberta                                                Oct. 2018 to Dec. 2018

Department of Electrical and Computer Engineering – Faculty of Engineering – University of Alberta

• Teaching and Research Assistant                                                                 Jan. 2010 to Aug. 2016

Electrical Engineering Department – Faculty of Engineering - Port Said University

Publications

1. M. Nashaat, R. Amin, Ahmed Eid, Rabab F. Abdelkader. "An Enhanced Transromer-based Framework for Interpretable Code Clone Detection." The Journal of Systems & Software (2025).
2. M. Nashaat, J. Miller. " Refining software defect prediction through attentive neural models for code understanding." The Journal of Systems & Software (2025).
3. M M. Nashaat, R. Amin, Ahmed Eid, Rabab F. Abdelkader. "Enhancing Large Language Models for Improved Code Clone Detection: A Fine-Tuning Approach." International conference on WorldS4 (2024).
4. M. Nashaat, J. Miller, "Towards Efficient Fine-Tuning of Language Models With Organizational Data for Automated Software Review," in IEEE Transactions on Software Engineering, vol. 50, no. 9, pp. 2240-2253, Sept. 2024, doi: 10.1109/TSE.2024.3428324
5. M. Nashaat, Heba Nashaat. "Utilizing Deep Reinforcement Learning for Resource Scheduling in Virtualized Clouds." International Work-Conference on Bioinformatics and Biomedical Engineering. Cham: Springer Nature Switzerland, 2023.
6. Mohamed M Ibrahim, M. Nashaat, "Online Customer Engagement as A Mediating Variable Between Social-Media Marketing and Customer Satisfaction: Using Big Data Analytics and Natural Language Processing", Journal of Contemporary Commercial Studies, 2023, pp. 1-34.
7. M. Nashaat, IE Shaalan, H Nashaat, "LTE Downlink Scheduling with Soft Policy Gradient Learning," in Proc. International Conference on Advanced Machine Learning Technologies and Applications, 2022.
8. W Moussa, M Nashaat, W Saber, R Rizk, "Comprehensive Study on Machine Learning-Based Container Scheduling in Cloud," in Proc. International Conference on Advanced Machine Learning Technologies and Applications, 2022.
9. M. Nashaat, A. Ghosh, J. Miller, and S. Quader, "Semi-Supervised Ensemble Learning for Dealing with Inaccurate and Incomplete Supervision," ACM Transactions on Knowledge Discovery from Data, 2021.
10. M. Nashaat, A. Ghosh, J. Miller, and S. Quader, "TabReformer: Unsupervised Representation Learning for Erroneous Data Detection," ACM/IMS Transactions on Data Science, 2021.
11. M. Nashaat, and J. Miller, "Improving news popularity estimation via weak supervision and meta-active learning," in Proc. Hawaii International Conference on System Sciences 2021 (HICSS), 2021.
12. A. Ghosh, M. Nashaat, J. Miller, and S. Quader, "Context-Based Evaluation of Dimensionality Reduction Algorithms – Experiments and Statistical Significance Analysis," ACM Transactions on Knowledge Discovery from Data (TKDD), 2021.
13. R.F. Abdel-Kader, M. Nashaat, M.I. Habib, H. M. K. Mahdi, "Automated server-side model for recognition of security vulnerabilities in scripting languages," International Journal of Electrical and Computer Engineering (IJECE), 2020.
14. M. Nashaat, A. Ghosh, J. Miller, and S. Quader, "WeSAL: Applying Active Supervision to Find High-quality Labels at Industrial Scale, " in Proc. Hawaii International Conference on System Sciences 2020 (HICSS), Maui, Hawaii, USA., 2020, pp. 219-228.
15. A. Ghosh, M. Nashaat, J. Miller, and S. Quader, "VisExPreS: A Visual Interactive Framework for User-driven Evaluations of Embeddings," IEEE Transactions on Visualization and Computer Graphics, 2020.
16. A. Ghosh, M. Nashaat, J. Miller, and S. Quader, "Interpretation of Structural Preservation in Low- dimensional Embeddings," IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.
17. M. Nashaat, A. Ghosh, J. Miller, and S. Quader, "Asterisk: Generating Large Training Datasets with Automatic Active Supervision," ACM Transactions on Data Science (TDS), vol. 1, no. 2, May 2020, doi: 10.1145/3385188.
18. M. Nashaat, A. Ghosh, J. Miller, and S. Quader, "M-Lean: An End-to-end Development Framework for Predictive Models in B2B Scenarios," Information and Software Technology, vol. 113, 2019, Pages 131-145, doi: 10.1016/j.infsof.2019.05.009.
19. A. Ghosh, M. Nashaat, and J. Miller, "The Current State of Software License Renewals in The I.T. Industry," Information and Software Technology, vol. 108, pp. 139–152, 2019.
20. M. Nashaat, A. Ghosh, J. Miller, S. Quader, C. Marston, and J-F. Puget, "Hybridization of Active Learning and Data Programming for Labeling Large Industrial Datasets," in Proc. IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, 2018, doi: 10.1109/BigData.2018.8622459.
21. A. Ghosh, M. Nashaat, J. Miller, S. Quader, and C. Marston, "A Comprehensive Review of Tools for Exploratory Analysis of Tabular Industrial Datasets," Visual Informatics, vol. 2, pp. 235–253, 2018.
22. M. Nashaat, K. Ali, and J. Miller, "Detecting Security Vulnerabilities in Object-Oriented PHP Programs," in Proc. IEEE 17th International Working Conference on Source Code Analysis and Manipulation (SCAM), Shanghai, China, 2017, pp. 159-164. doi: 10.1109/SCAM.2017.20.