Data Science & Machine Learning | CS Student @ University of Pécs 🇭🇺

I am a final-year Computer Science student and Stipendium Hungaricum Scholar focused on building machine learning models, automated data pipelines, backend architectures, and handling complex, imbalanced datasets.

👨‍💻 About Me

• 🎓 Completing my B.Sc. in Computer Science (Graduating July 2026).
• 📊 Focused on Data Science, ML in healthcare, and AI.
• 🌍 Multilingual (Fluent in Hindi/Urdu and English).
• 🚀 Currently seeking AI/ML or Backend Engineering internships in Europe.

Data Science & Machine Learning

Software Engineering & Web

Diabetes Prediction ML Predictive modeling pipeline utilizing clinical survey datasets (BRFSS) to predict diabetes onset.

• Engineered models (XGBoost, Random Forest, Logistic Regression) on datasets exceeding 250K records.
• Handled severe class imbalance (up to 46:1) using ADASYN, class weighting, and custom threshold tuning.
• Prioritized minority-class detection, successfully improving recall from 0.28 to 0.88.

University Administration API A robust RESTful backend system built to handle administrative workflows and secure data processing.

• Architected a strict N-tier application (Controller, Service, Repository) using Java and Spring Boot.
• Integrated MySQL for secure relational data persistence and custom reporting.
• Automated API endpoint documentation using OpenAPI/Swagger.

AQI Prediction Dashboard An end-to-end machine learning pipeline and interactive dashboard forecasting Air Quality Index (AQI) levels for the Tharparkar district.

• Engineered an automated data pipeline to programmatically ingest real-time meteorological data via the OpenMeteo API.
• Processed live JSON payloads to feed pre-trained ML models, eliminating reliance on static datasets for dynamic inference.
• Developed and deployed a live visual interface to present real-time environmental parameters and predictive metrics.

📫 Connect With Me LinkedIn · Portfolio Website