Nitya Choudhary

Machine Learning • AI • Image Processing

B.Tech Information Technology @ IGDTUW (GPA 8.6). Currently an ML Intern at DRDO–ISSA Lab, working on satellite image intelligence, clustering and classification pipelines for wargaming and strategic analysis systems.

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Technical Skills

Machine Learning, Model Evaluation
Deep Learning (CNNs, Transformers)
Computer Vision, Image Processing
Python, NumPy, Pandas
TensorFlow, PyTorch, Scikit-Learn

Projects

NeuroTrace – Brain Tumor Detection

Developed a CNN-based medical image classification system achieving 96% accuracy on MRI scans. Implemented preprocessing, data augmentation, and performance evaluation.

GitHub | Demo

NutriLens – AI Nutrition Analysis

Built an AI pipeline combining OCR and language models to analyze food labels and generate nutritional insights for health-focused users.

GitHub

Weather Forecast Web App

Developed a responsive weather application using APIs, JavaScript OOP, and modern UI principles with dark/light modes.

GitHub

Research & Experience

DRDO – ISSA Lab (Ongoing)

Working on satellite imagery analysis for defense applications, focusing on clustering, classification, and pattern recognition for wargaming and strategic simulations.

ACM IGDTUW – Research Intern

Conducted NLP research using transformer models (DistilBERT) for semantic analysis tasks, achieving ~90% accuracy.

Research & Technical Notes

Satellite Image Processing

Explored preprocessing, normalization, and feature extraction techniques for satellite imagery to improve ML model robustness.

Unsupervised Learning in Defense

Applied clustering algorithms such as K-Means and DBSCAN to group spatial ship formations from satellite data.

ML Model Evaluation

Focused on metrics such as precision, recall, F1-score, and confusion matrices for reliable deployment.

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