- Processed and analyzed sequencing data that identified RNA editing sites among other sequencing characteristics to help characterize a novel gene in neurodevelopmental disorders.- Discovered and applied suitable open-source RNA editing software for the analysis of RNA-seq data through the utilization of bash scripts on a high-performance computing cluster.- Developed a comprehensive pipeline to convert in-house exome data from hg19 to new reference standard hg38 including data quality control for further variant identification and analysis.- Organized and wrote detailed documentation on Github such that results could be easily reproduced.

- Applied unsupervised learning methods and dimensionality reduction techniques to dynamic metabolism measurements from Hyper-polarized Carbon-13 MRI for in-vivo heart disease detection - Implemented various dimensionality reduction techniques including PCA, ICA, t-SNE, and UMAP and identified the best technique to represent the data- Met with mentor multiple times per week to discuss areas for model performance improvement

- Applied deep learning methods including Graph Convolutional Neural Networks for drug property prediction (ADMET) of small molecules

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