PROFILE SUMMARY

Maham is a highly capable Lab Instructor at Shifa Tameer-e-Millat University (STMU), holding an M.S. in Software Engineering (COMSATS University Islamabad) and a B.S. in Information Technology (GCWUS Sialkot). She brings a robust and versatile technical foundation, with deep expertise in Software Engineering, Artificial Intelligence, Machine Learning, eXplainable AI, Artificial Neural Networks (ANN), Object‑Oriented Programming (OOP), and advanced Proficiency in Python and Java. In her current academic role, she has guided BS‑AI students in foundational and advanced courses such as Knowledge Representation & Reasoning (KRR), OOP, andANN), fostering both their theoretical understanding and practical skills. Beyond conventional teaching, Maham has led technical workshops for medical professionals, including MBBS doctors, dentists, and medical scholars where she taught Python programming and demonstrated applications of AI in healthcare settings. Her research interests are focused and socially relevant: she works on ML‑based risk assessment models, XAI‑driven interpretability studies, construction analytics, and AI‑assisted clinical decision support. By interweaving academic instruction, hands‑on programming, and applied research, Maham strives to build a bridge between computing theory and real-world problem solving, preparing students to excel both in academia and industry, and contributing to technological innovation with a socially conscious mindset.

RESEARCH AREAS / INTERESTS

Research on XAI-integrated ML models for risk assessment in software engineering and construction project delay prediction. Experience with ML models including SVM, LR, RF, DT, NB, and ANN. Skilled in interpretability techniques such as SHAP, Ablation, Saliency Maps, and Permutation Feature Importance.

1. XAI (SHAP, Ablation, Saliency, PFI)
2. Machine Learning (ML) Models
3. ANN, CNN, LSTM
4. Java (teaching), Python
5. Dataset analysis and preprocessing
6. Academic writing and workshops