Aleena Shakil

Final year Software Engineering student (CGPA 3.71/4.00) with a keen interest in applied computer vision and machine learning. Currently completed a production style banknote recognition and counterfeit detection pipeline at the State Bank of Pakistan using PyTorch, OpenCV, and OCR. Comfortable across the ML workflow such as data preprocessing, model training and evaluation, and deployment-oriented tooling with a growing interest in research-driven problem solving alongside hands-on project building.

Summer Intern - State Bank of Pakistan (SBP) - Karachi, Pakistan

(2026-06 - 2026-08)

IT & Project Management Dept.

• Built and evaluated a deep learning classification model in PyTorch to recognize denominations across a dataset of 7,500+ banknote images, using accuracy and confusion matrix analysis to guide iterative model improvement.
• Developed an OCR-based text extraction pipeline with PaddleOCR and OpenCV, applying perspective correction and background removal to improve read accuracy on scanned notes.
• Contributed to a counterfeit detection pipeline by implementing computer vision preprocessing steps, supporting testing against real and simulated counterfeit samples.
• Collaborated with a cross functional team using Git for version control, documenting model iterations and performance findings to support project handoff.

Teaching Assistant - Sir Syed University of Engineering & Technology - Karachi, Pakistan

(2025-10 - 2026-01)

• Supported programming and ICT lab sessions, debugging code and explaining core concepts in real time.
• Reviewed and graded assignments, identifying recurring logic errors and giving targeted feedback.

BS - Software Engineering - Sir Syed University of Engineering & Technology (SSUET) (2023 - 2027)