I am Faiza Khan, a Lecturer at the National University of Technology (NUTECH), Islamabad, specializing in Artificial Intelligence and Software Engineering. With over six years of combined teaching and research experience, my expertise includes Machine Learning, Deep Learning, and Natural Language Processing.
Currently pursuing my PhD in AI, my research focuses on intelligent systems for healthcare and predictive data modeling. My teaching approach emphasizes strong theoretical foundations alongside practical, hands-on skills to prepare students for real-world AI applications.
Lecturer, Department of AI & Software Engineering, National University of Technology (NUTECH), Islamabad (2025–Present)
Teach undergraduate courses in Artificial Intelligence, Machine Learning, and Software Engineering.
Advise students on academic, research, and final-year projects related to AI and data-driven systems.
Contribute to departmental quality assurance processes as a member of the Quality Enhancement Cell.
Research Assistant (Remote) (2019–2023)
Conducted research in Machine Learning and Deep Learning under international collaboration.
Developed advanced algorithms for hyper-parameter optimization and feature selection using Artificial Immune Networks.
Contributed to high-impact publications in areas such as software bug prediction, NLP, and healthcare AI systems.
Teacher & Section Head, Scouts Public School, Swabi (2018–2020)
Delivered lectures and managed academic activities across multiple subjects.
Monitored student performance and coordinated with parents for academic improvement.
Led section-level academic planning and collaborated with faculty to enhance educational outcomes.
Ph.D. in Artificial Intelligence (In Progress), National University of Sciences and Technology (NUST), Islamabad, Pakistan (Expected 2031)
M.S. in Software Engineering, Riphah International University, Islamabad, Pakistan (2019)
B.S. in Software Engineering, International Islamic University, Islamabad, Pakistan (2016)
B.Ed., Allama Iqbal Open University, Islamabad, Pakistan (2023)
I have contributed to multiple peer-reviewed publications in reputed journals and conferences, including IEEE Access and other international venues, with research focused on Machine Learning, Deep Learning, Natural Language Processing, and AI-driven healthcare systems.
I have taught a variety of undergraduate-level courses in the AI Department. Below are the courses I have been involved in teaching:
- Database Systems
- Data Structures
- Object-Oriented Programming
- Machine Learning
My research focuses on Machine Learning, Deep Learning, and Natural Language Processing, with particular emphasis on predictive data modeling and intelligent decision-support systems. I have worked on advanced techniques such as hyper-parameter optimization and feature selection using Artificial Immune Networks, improving the performance and accuracy of machine learning models.
My work also explores the application of AI in healthcare, including disease prediction, diagnosis support, and treatment planning through data-driven approaches. Additionally, I have contributed to research in software bug prediction and Urdu sentiment analysis using deep learning methods.
Looking ahead, I am interested in integrating AI with real-world domains such as healthcare and intelligent automation systems. My goal is to develop robust, scalable, and efficient AI solutions that enhance predictive capabilities and support informed decision-making.
Publications (Selective)
- Khan, F., Kanwal, S., Alamri, S., & Mumtaz, B. (2020). Hyper-Parameter Optimization of Classifiers Using Artificial Immune Network. IEEE Access.
- Mumtaz, B., Kanwal, S., Alamri, S., & Khan, F. (2021). Feature Selection Using Artificial Immune Network for Software Defect Prediction. Intelligent Automation and Soft Computing.
- Sehar, U., Kanwal, S., et al. (2021). Urdu Sentiment Analysis via Multimodal Deep Learning. IEEE Access.
- Kanwal, S., Khan, F., et al. (2022). AI-Based Clinical Decision Support System for COVID-19 Detection. International Journal of Imaging Systems and Technology.
- Khan, M., et al. (2025). Multilingual Emotion Detection using Adaptive Models (SemEval-2025). Proceedings of International Workshop on Semantic Evaluation
