BS Computer Science, Thal University Bhakkar

Coursework: Artificial Intelligence, Machine Learning, Database Systems, Data Structures and Algorithms, Distributed Computing, Software Engineering, Cybersecurity, Computer Networks, Operating Systems.

Intermediate (F.Sc), BISE Sargodha

Matriculation (SSC), BISE Sargodha

Hospital Management System (Final Year Project)

• Designed and deployed a full-stack hospital management system with secure authentication and role-based access.
• Implemented patient records, appointment scheduling, and CRUD operations on a relational MySQL database.

Machine Learning Classification Pipeline

• Built an end-to-end supervised pipeline: preprocessing, feature engineering, Random Forest and SVM.
• Tuned hyperparameters with GridSearchCV, reaching 92%+ accuracy, an 8% gain over the baseline.

Credit Card Fraud Detection

• Developed a machine learning system to detect potentially fraudulent credit card transactions using supervised and unsupervised learning approaches.
• Performed data preprocessing, feature scaling, feature selection, and exploratory data analysis (EDA) to examine fraudulent and legitimate transaction patterns.
• Implemented a Random Forest Classifier for supervised fraud detection and Isolation Forest for unsupervised anomaly detection.

ITU University Network Design

• Designed a multi-campus university network with VLAN-based segmentation, inter-VLAN routing, and dynamic IP allocation.
• Configured RIPv2, DHCP, trunking, and cloud connectivity to provide scalable and secure network communication.

IT Directorate Intern, LESCO

• Assisted with software and database-related tasks within the IT Directorate.
• Worked with Oracle Database and SQL on enterprise data systems.
• Collaborated with technical teams on enterprise applications.

Data Science Intern, 10Pearls

• Developed AQI Predictor, a Python-based machine learning project to predict the Air Quality Index (AQI).
• Used Python libraries, including Pandas, NumPy, and Scikit-learn, for data processing and machine learning model development.
• Used SciPy and Joblib to support scientific computing and machine learning workflows.

A Comparative Benchmark of SQL and NoSQL Databases for Read/Write Performance Under Different Indexing and Cache Conditions

KIET Journal of Computing and Information Sciences · Journal website