Shafin Ahmed
Machine Learning | Bioninformatics | Research | Teaching
BRAC University
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Deep generative framework to integrate RNA, ATAC, proteomics and metabolomics data where each dataset has only some modalities. Uses modality-specific encoders and decoders with a shared latent space, plus missing-not-at-random (MNAR) modeling. Adds calib
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Evaluated Platt scaling and isotonic regression for tree-based models on binary and multiclass healthcare tasks. Used the CDC Diabetes Health Indicators 2023 data with ROC-AUC, Brier score, ECE and reliability diagrams.
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Built a pipeline to classify breast cancer samples from high-dimensional RNA-seq data (TCGA-BRCA). Used log transform and mutual-information feature selection, then compared Logistic Regression, XGBoost and a Neural Network under class imbalance.
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