Aina Hyder

I’m a B.Sc. Computer Science & Information Technology student specializing in Machine Learning and Data Engineering, with hands-on experience designing predictive models, ETL pipelines, data warehouses, and retrieval-augmented LLM systems.

In my internships, I’ve built end-to-end ML workflows for real-world prediction (including AQI forecasting), improving prediction accuracy by 12% through hyperparameter tuning and cross-validation, and strengthening robustness with feature engineering and overfitting controls. I’ve also automated reporting workflows—cutting manual effort by 35%—and optimized backend queries to improve response time by 25%.

For my FYP, I led an AI Health Assistant team to implement a RAG pipeline (FAISS + LangChain), improving contextual relevance by 25% while reducing hallucinations using structured chunking, retrieval evaluation, and grounded responses. I’m driven by scalable, accuracy-focused solutions—and I thrive when turning data into reliable, user-facing systems.