Ello!
I'm an MSc Advanced Data Science student at the University of Exeter, passionate about turning messy, real-world data into models and systems that actually solve problems. My work spans computer vision, deep learning, and classic ML — from building a drone-based litter detection system that helps city councils prioritize beach and park clean-ups, to developing a deepfake detection model with 85% recall for my undergraduate research.
Before Exeter, I worked hands-on with Python, TensorFlow, and PyTorch to build models for customer segmentation, employee turnover prediction, and dynamic pricing — several achieving 95%+ accuracy in production-style settings. I enjoy the full pipeline: cleaning and wrangling data, building and evaluating models, and communicating insights in a way non-technical stakeholders can act on.
Education
MSc Advanced Data Science
University of Exeter, England 2025 – PresentWorkshop Leader — ExCode
- Assisted students in workshop sessions to solve Python programming exercises as part of ExCode, a free student-led 7-week Python Bootcamp.
- Bootcamp backed by Google Student Developer Club and the UoE Computer Science Society at the University of Exeter.
Research Project: Detecting Litter in Drone Imagery Using Computer Vision Techniques
- Capturing aerial footage of UK parks and beaches using drone-mounted cameras.
- Applying computer vision techniques to detect litter in images and video frames.
- Generating interactive hotspot maps to help city councils identify high-litter zones and prioritise clean-up operations.
BS Computer Science
Virtual University of Pakistan, Pakistan 2019 – 2023Final Year Project: Deepfake Detection by Deep Learning Methodologies
- Developed a deep learning model to detect AI-generated deepfake content in images and videos.
- Achieved 85% recall in identifying face swaps and voice swaps produced by generative models.
- Employed convolutional and recurrent architectures to analyse both spatial and temporal features.
Projects
Deepfake Detection Using Deep Learning (FYP)
Model can predict a fake video generated using (A.I) deep learning with 85% Recall. Model has the ability to detect voice and face swap.
View on GitHubAZB Colony Billing System
Web-based billing management system for AZB Colony residents. Features login-protected access with Admin and User roles, monthly billing tracking (consumption, rates, arrears), bill search, and payment recording with partial/full payment support. Built with Python/Flask, SQLite, and vanilla HTML/CSS/JS.
View on GitHubCustomer Segmentation Based On Annual Spending
Model can classify with precision of 95% that a customer belongs to a specific category, it is further used for recommending products, deals, promotions.
View on GitHubEmployee Turnover Monitoring Model
Model can successfully predict with 97% accuracy based on several features such as promoted in last 5 years, pay, weekly hours etc. whether the employee will leave the company or not.
View on GitHubCustomised Train Ticket Price Predictor
Price of the ticket can be predicted with 94% precision, pricing is changed regularly based on demand and time. Data is scraped regularly and it can be predicted what the fare will be given destination, origin, class of train etc.
View on GitHubExperience
Data Science & Machine Learning Trainee
Dice Analytics Feb 2025 – Apr 2025- Built foundational expertise in machine learning concepts, data pipelines, and statistical analysis.
- Performed data ingestion and ETL processes to collect, clean, and structure raw datasets for analysis.
- Applied Python programming for data manipulation, preprocessing, and analytical workflows.
- Conducted data wrangling and exploratory data analysis (EDA) to identify patterns, trends, and data quality issues.
- Communicated analytical findings through clear data storytelling and visualization techniques.
- Explored datasets to support problem identification, hypothesis generation, and data-driven decision making.
Accounts and IT Officer (Hybrid)
AZB Colony Oct 2023 – Aug 2025- Designed and implemented an automated monthly billing system, reducing bill generation operations from 2 days to just 3 hours.
- Oversaw daily accounts of the colony, managing bookkeeping, filing systems, and billing operations.
Convergent Graduate Academic Program (CGAP)
Convergent Business Technologies Aug 2023 - Sep 2023- Completed CS50: Introduction to Computer Science (HarvardX) as part of the program, establishing a solid foundation in core computer science concepts.
- Developed proficiency in programming fundamentals, algorithms, data structures, and key computational principles.
- Applied computational thinking and structured problem-solving techniques to analyse and solve programming challenges.
- Completed rigorous coding assignments and problem sets designed to strengthen logical reasoning and algorithmic efficiency.
- Enhanced ability to design, implement, and optimise solutions to complex computational problems.
Project Intern
Global Consulting Services May 2023 - Jun 2023- Learned and worked with BIRT (Business Intelligence and Reporting Tools) for report generation.
- Gained hands-on experience in SQL for querying and managing databases.
- Explored IBM Maximo, understanding its role in enterprise asset management.
Skills
Programming Languages
- Python
- SQL
- R
- HTML
- CSS
Data Analysis & Tools
- NumPy
- Pandas
- Power BI
- RegEx
- Git
Machine Learning
- TensorFlow
- Scikit-learn
- Snap ML
- PyTorch
Business Intelligence
- BIRT (Business Intelligence and Reporting Tools)
Certifications & Trainings
Stanford University
- Generative AI for Everyone
- Machine Learning Specialization
- Supervised Machine Learning: Regression and Classification
- Advanced Learning Algorithms
- Unsupervised Learning, Recommenders, Reinforcement Learning
Harvard University
- CS50's Introduction to Programming with Python
- CS50's Introduction to Computer Science
Dice Analytics
- Data Science and Machine Learning
Kaggle
- Introduction to Deep Learning