About

I'm a bioinformatics software engineer specializing in building sophisticated, production-grade applications for proteomics research. As the lead developer of NULISA Analysis Software (NAS), I design and implement complex systems that empower researchers to unlock insights from sequencing-based proteomics data.

My work bridges the gap between cutting-edge science and practical software engineering. With three master's degrees—Industrial Engineering, Data Science, and Executive Data Analysis—I bring a uniquely comprehensive perspective combining operational excellence, advanced analytics, and strategic data leadership.

With expertise spanning R Shiny development, Docker containerization, SQL database engineering, and proteomics sequencing data analysis, I bring a full-stack approach to scientific software development. I'm passionate about creating modular, scalable architectures that not only solve today's challenges but are built to evolve with tomorrow's requirements.

Foundation in systems optimization, process improvement, and quantitative analysis.

Advanced statistical methods, machine learning, and computational analysis. Developed MSstats Sample Size Shiny application for proteomics experimental design during this program.

Strategic approaches to data-driven decision making and analytics leadership.

Leading development of NULISA Analysis Software (NAS), a complex, modular R Shiny application for proteomics data analysis. Architecting scalable solutions and contributing to the NULISAseqR package.

• Lead developer of NAS - a highly sophisticated analysis platform with modular architecture
• Designed and implemented Docker containerization with Azure Kubernetes Service deployment
• Manage CI/CD pipeline including Kubernetes manifests, automated testing, and Azure Container Registry
• Integrated testthat unit tests as deployment gates with renv environment management
• Engineered novel multi-plate merging pipeline and ETL infrastructure for NULISAseqR package, enabling project-level analysis capabilities that didn't previously exist
• Created automated QC systems and visualization dashboards

Provided critical statistical analysis support for clinical studies while developing intuitive Shiny applications that empowered bench scientists to visualize and analyze proteomics data independently. Worked with mass spectrometry-based proteomics and single-cell RNA sequencing (scRNAseq) datasets.

• Supported statistical analysis for multiple clinical studies
• Developed Shiny applications enabling bench scientists to visualize proteomics data
• Built tools for basic statistical analysis accessible to non-statisticians
• Worked with challenging datasets including mass spec proteomics and scRNAseq data
• Proposed out-of-the-box solutions and built toolbox of statistical methods
• Bridged the gap between complex statistical methods and user-friendly interfaces

Completed two co-op rotations with the Energy Markets Team, developing analytical tools and web applications for demand response program operations. Worked with geographically distributed teams across new and old energy markets.

• Designed mission-critical improvement to settlement process involving UI development and database management
• Developed UTI web application for inspecting and identifying interval meter data
• Built analytical tools for enrollment, nomination, and settlement processes
• Created R-Shiny dashboards for monitoring customer participation in Demand Response programs
• Resulted in dramatic increase in efficiency of key operational processes
• Collaborated with cross-functional, geographically distributed teams