Center for Data Driven Discovery in Biomedicine (D3b)
Daniel Kolbman is a Data Engineer responsible for designing systems which enable scientific research through the use of data. He works alongside scientists and other engineers to devise methods and workflows to store, analyze, and distribute the data arising from the latest studies in cancer and rare diseases. Daniel also works to find ways to maximize impact of existing data through enrichment and harmonization.
Prior to joining CHOP in November of 2017, Daniel worked on the NIH Genomic Data Commons at the University of Chicago Center for Data Intensive Science. He was responsible for the data-intensive task of integrating clinical data with the results of harmonized calling pipelines to support cohort filtering and immediate exploratory analysis in real-time straight from the browser. He also developed computational models of cells using high-performance methods to investigate the dynamics of metastatic cells in breast cancer.
Daniel earned a BSc in Physics from the Rochester Institute of Technology. He is committed to catalyzing discoveries through the promotion of data accessibility and the application of proven engineering practices.