Led a diverse team of developers, bioinformaticians, and interns, in continuous development of a cloud-native bioinformatic software that accelerates research teams through streamlined, scalable, and interoperable genomic workflows.Spearheaded initiatives leading to a tenfold increase in workflow capacity, integration of nf-core pipelines, design of AI (LLMs) integration into product, enhancing data visualization and reporting, and tailoring custom workflow solutions for client-specific needs.Engaged with customers to gather feedback for engineering tasks, design custom workflows, analyze data, and interpret results.Coordinated with design, frontend, and backend development teams to conceptualize, develop, and launch new product features.Documented and maintained guidelines for platform usage and pre-built pipelines.Initiated and led the integration of a third-party company to increase our capabilities in incorporating open-source tools and workflows.Partnered with the business development team to produce case studies, author blog posts, and engage with customers, amplifying the company's market presence.Worked closely with the sales team, providing expert product and bioinformatics insights throughout the sales cycle, leading to a sevenfold increase in customer acquisition.

Collaborated with an interdisciplinary team to develop a platform that enables users to create reproducible, scalable, robust, and efficient workflows for large-scale genomic data analysis.Designed and implemented a Python-based package for managing and building Docker images, wrapping open-source tools, and interfacing with backend workflow language, enhancing the platform's capability to execute tools and workflows.Contributed to transitioning an IBM-incubated project into an independent standalone company.

Collaborated with TEDDY research group faculty and staff to design and maintain open-source software, scripts, and automated pipelines, enhancing research and development processes.Developed, documented, and managed Snakemake data analysis pipelines and workflows.Provided comprehensive programming and analytical support across various bioinformatics projects, including GWAS, RNAseq, variant calling, imputation, structural variants, and microbiome studies.Partnered with IT leadership to create a predictive deep learning model (LSTM) for early Type 1 Diabetes diagnosis, leveraging clinical and RNAseq time-series data.

Use of CRISPR CAS9 system to investigate deletion of large genome pieces in miceDevelopment of pipeline for 3D visualization of genomic regions of mouse chromatin structures from Hi-C datasets using python based librariesBuilt custom scripts for data analysis and processing

Research on development and activation of B cells and T cells in both the primary and memory responseUse of fluorescence activated cell sorter (FACS) to analyze and sort cells based off florescent markersAnalysis of immunological data sets, using computational programs for data visualization Genotyping of mice for use in experiments and for breeding purposes

Circadian research of master regulatory clock genes, specifically Connexin 36, and its role in mice under behavioral and sociological conditionsUse of program, MetaMorph, to analyze neuronal single cells for quantification and analyze