Hi, I'm Atifa Nawaz

Built an AI research assistant capable of processing PDFs, DOCX files, and online paper links to provide context-rich answers. Integrated LangChain, FAISS, and LLaMA 3 for retrieval-augmented generation and citation-aware responses. Implemented document parsing, embedding, and inline citation injection for accurate and verifiable results. Developed a robust question-answering pipeline with semantic search over document embeddings.

Developed an AI-powered chest X-ray diagnostic web application using CNNs for classification. Implemented explainable AI visualizations using GradCAM++ to highlight regions of interest for model predictions. Deployed a Streamlit interface enabling real-time image upload, prediction, and interactive visualization for research and educational purposes.

Developed an Artificial Neural Network (ANN) to predict loan defaults using historical loan data, handling imbalanced datasets with SMOTE and scaling numeric features. Designed the ANN architecture with dense layers, ReLU activations, batch normalization, dropout, and a sigmoid output layer for binary classification. Evaluated model performance using Accuracy, Precision, Recall, F1-Score, and AUC, achieving high recall (0.8927) to minimize risk and visualized results with ROC curves and training history plots.

CNN model identifying plant leaf diseases from the PlantVillage dataset (20,000 images, 38 classes). Implemented preprocessing, data augmentation, and evaluation metrics including confusion matrix and classification report for agricultural diagnostics.

Regression ANN predicting arrival delays using historical flight data. Handled feature engineering, categorical encoding, and outlier management achieving MAE of 1.83 minutes and R² score of 0.9662.

Binary classification ANN predicting next-day stock price movements using technical indicators (RSI, MACD, Bollinger Bands). Achieved 0.768 accuracy with F1-score of 0.786 and class weight handling for imbalanced data.