Dhruv Khatri
I specialize in computational biology, machine learning, and software development to solve complex biological problems and advance scientific research.
About Me
I'm a computer and data scientist with a focus on applying computational techniques to solve challenges in biomedical and biological research. With a foundation in computer science, data engineering, and molecular biology, I specialize in designing scalable algorithms and analytical tools to extract insights from high-dimensional biological datasets.
My work spans machine learning applications in healthcare, large-scale genomic data analysis, and the development of AI-driven pipelines for predictive modeling. I'm especially interested in single-cell omics, integrative multi-modal analysis, and leveraging deep learning to advance our understanding of protein function, gene regulation, and disease mechanisms.
In my free time you can catch me playing basketball and golf, trying out new restaurants, or driving around southern California. I love exploring new places and experiences which push me out of my comfort zone.
Experience & Skills
My professional journey combines academic research, industry experience, and continuous learning in the rapidly evolving fields of bioinformatics and data science.
Undergraduate Research Assistant - Bafna Lab
UCSD Computer Science and Engineering
· Exploring the role of ecDNA on gene knockout results in various cancer cell lines using AmpliconArchitect.
· Developed gene networks using Cytoscape .js tools to visualize co-amplification events and utilized python libraries for data analysis and statistical testing.
Research and Development Intern
Eli Lilly and Company
· Utilized AI and computational tools for protein design and engineering to enhance early large molecule discovery pipeline.
· Communicated findings in a 30-minute oral presentation to technical stakeholders and executive leaders along with 23 page report in Nature research format.
Undergraduate Research Assistant - Rana Lab
UCSD School of Medicine
· Developed a single-cell RNA-seq 10x pipeline using Linux and R to analyze sequenced mouse bone marrow cells for mRNA vaccine study, working with interdisciplinary team of biologists.
· Data-mined TCGA and GTEx databases to provide insight into gene expression trends across 13 different cancers for ongoing projects.
· Collaborated with a team of bioinformaticians to optimize pipeline shell scripts for use on remote supercomputer.
· Developed in-depth tutorials on GitHub for future lab bioinformaticians to understand pipelines and workflow.
Research Study Assistant
UCSD Health - Moores Cancer Center
· Assisted in administration of California Educator Tobacco Survey (CETS) with 2,000+ participating schools and 100,000+ participants in collaboration with California Department of Education.
· Developed a database of school contact information, designed survey using Qualtrics, and distributed to participants using Qualtrics API.
· Continued to follow up on survey results, regularly cleaning data and generating visualizations to present and publish findings.
Featured Projects
