Xsolis

• Developed a retrieval-augmented generation LLM chat application for assisting the Xsolis physician advisor team in efficiently reviewing patient cases
• Built an inpatient status model explainer service that utilizes counterfactual explanations to interpret predictions
• Designed a QC monitoring app to compare inpatient status predictions across different model iterations, deploying each model as a containerized API service
• Produced a functional workflow for labeling unlabeled datasets using weakly supervised learning
• Researched and prototyped diverse deep learning model architectures for optimizing the performance of Xsolis' discharge disposition model

Data Scientist

Nashville Software School

• Taught students data science, statistical modeling, and machine learning techniques in Python, R, and SQL
• Provided technical guidance to students based on real-world scenarios and industry best practices

Data Science Assistant Instructor

Nomi Travel

• Designed a knowledge-based recommender system for providing personalized recommendations for where to eat, drink, and go in the city
• Developed web scraping workflows to capture recommendation insights from hundreds of thousands of local reviews using NLP techniques
• Built a real-time analytics dashboard using R Shiny to monitor user recommendations, recommender system KPIs, and data quality assurance

Intensive bootcamp focusing on data science fundamentals and problem solving. Leveraged real-world datasets to develop analyses, data tools, and models to inform community business partners' strategic decision-making. Select project highlights can be viewed at datascienceportfol.io/rohit.

Data Science Fellow

Vanderbilt University

Thesis: "High-Throughput Epitope Determination of HIV-1 Polyclonal B Cell Repertoires"

• Developed a novel genomic data pipeline in R for processing, analyzing, and interpreting high-dimensional single-cell sequencing data, successfully identifying epitope-specifi c broadly neutralizing HIV antibodies from infected donor samples
• Utilized statistical and machine learning techniques including dimensionality reduction, clustering, and hypothesis testing to determine the cellular identities of individual cells and genes that are differentially expressed between clusters of cells
• Adapted data analysis pipelines to high-performance computing environments, enabling parallel processing of hundreds of genomic datasets

Graduate Research Assistant

• Curated and performed statistical analyses on gene expression and genetic variation data using R, Bash scripts, and Linux command line tools
• Wrote Excel user-de fined functions using VBA in order to analyze data generated by experiments

Research Assistant

Vanderbilt University Medical Center

As a biomedical researcher turned data scientist, I leverage my quantitative research background to tackle complex problems and deliver novel insights to stakeholders. I bring a proven track record of being a detail-oriented problem solver and a team player.

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