I'm a data scientist and computational biologist, with a strong academic background in Data Science, Molecular and Cell Biology, and Business Administration from the University of California, Berkeley. With over 3 years of industry experience, I specialize in leveraging machine learning techniques, multi-omics data analysis, and state-of-the-art bioinformatics tools to build innovative data-driven solutions.

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• Neural ODEs for Pharmacokinetics (PK) Modeling: Implemented a neural network model for state-of-the-art PK Modeling.
• Multi-omics Data Analysis Pipeline: Developed a pipeline to analyze next-generation sequencing (NGS) experiment data.
• Bioinformatics Target Identification Tool: Built a bioinformatics tool to analyze genomics data from Single cell/Bulk RNA Sequencing Experiments.
• Early Detection of ARDS Subphenotypes Using ML: Designed an ML Model to detect ARDS patient subphenotypes using baseline clinical data from Electronic Health Records.

• Credit Karma Longitudinal Car Sales Forecast: Constructed an LSTM model to forecast future sales trends using longitudinal data from 500,000+ used car purchase transactions.
• Customer Churn Patterns Analysis in Telecommunications Industry: Analyzed time-series data on customer churn patterns for a telecommunications company.
• Northwestern Mutual Millennial Client Demographic Data: Generated dynamic descriptive visualizations on millennium client demographic data.

• Molecular Cell Atlas of the Human Lung: Conducted analysis of Single-cell gene expression data of 116,314 cells from 20 frozen lungs.
• Biomarkers for Kidney Antibody-mediated Rejection (ABMR): Identified pathways and genes in ABMR Using Bulk RNA-Seq Data.

I'm always looking for ways to drive innovation through data. Let's connect and explore how we can collaborate on your next project.