I’m interested in machine learning, computational imaging, and scientific data analysis. My projects span image classification, segmentation, simulation, and high-dimensional data analysis, with applications in healthcare and biomedical research.
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Supervised Learning Fundamentals
Implementations of decision trees, SVMs, naive Bayes, and ensemble methods. -
Chest X-ray Classification Benchmark
Deep learning benchmark for image classification using CNN-based ensemble models.
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nnUNet Segmentation Benchmark
Automated 3D image segmentation with deep learning. -
Retinal OCT Classification
Image classification on retinal OCT scans for diagnostic prediction.
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Gene Expression Classification and Clustering
Classification and clustering of high-dimensional gene expression data. -
Monte Carlo and Molecular Dynamics
Simulation methods for complex physical and biomolecular systems.