I analyze biological data and apply statistical and machine learning methods in order to identify and enhance understanding of novel therapeutic targets and biomarkers. Here, my responsibilities include:

• Analyzing large-scale genome-wide association studies (GWAS) in cancer immunology clinical trial cohorts and real world data.
• Analyzing the roles of immunogenetic variations in determining survival and adverse events in cancer patients.
• Investigating the impact of inherited genetic variation on tumor evolution and mutational patterns.
• Performing integrated analyses of multidimensional molecular data sets to better understand anti-tumor immune responses.

At the Battle Lab, I worked to develop and use computational methods to understand, analyze and interpret gene regulation in humans. Here, my responsibilities included:

• Improving accuracy and interpretability of co-expression networks,
• Studying regulation of transcription and splicing using bulk and single-cell RNA-seq,
• Establishing best practices for co-expression and trans-eQTL analysis,
• Uncovering genetic effects on gene expression across diverse human tissues as part of two big consortia (GTEx and eQTLGen) and other collaborations, and
• Mentoring junior lab members.

At DMIS lab, my responsibility was to

• Develop methods to find disease-causing pathways or co-expressed genes using microarray gene expression profiles, and
• Create tools to visualize and interpret gene interactions.