Charlotte Darby
Research Scientist II, Computational Oncology
Massachusetts, United States
Summary
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Senior🎓
Top SchoolCharlotte Darby is a computational biologist and Research Scientist II in Computational Oncology at Takeda, bringing 11 years of experience bridging computer science and translational cancer research. She holds a PhD in Computer Science from Johns Hopkins and BS/MS degrees from Carnegie Mellon, and applies scalable analytics and AI/ML to omics across scales—from millions of single cells to first-in-human clinical data. Her work spans industry leaders (10x Genomics, IBM Research, New York Genome Center) and includes notable open-source contributions to Seurat, improving performance and reference-mapping tools used widely in single-cell genomics. At Takeda she builds bioinformatics infrastructure and coordinates stakeholders to translate complex data into therapeutic strategy, often focusing on immuno-oncology. Colleagues value her combination of rigorous algorithmic training, hands-on software development, and a clear patient-centered motivation that treats every data point as a responsibility.
11 years of coding experience
4 years of employment as a software developer
Johns Hopkins UniversityPennsylvania Leadership Charter School, University Scholars ProgramBachelor of Science (BS), Computational Biology, Bachelor of Science (BS), Computational Biology at Carnegie Mellon University
Github Skills (6)
rna-seq10
r10
data-structure9
algorithm9
data-structures9
algorithms9
Programming languages (7)
Github contributions (5)
satijalab/seurat
Jul 2020 - Oct 2020
R toolkit for single cell genomics
Role in this project:
Back-end Developer
Back-end DeveloperContributions:63 commits, 57 comments, 44 issues in 3 months
Contributions summary:Charlotte contributed to the Seurat R toolkit by making several significant changes to the code. They focused on improving the performance of the anchor scoring, adding comments to functions, and refactoring the code, which included adding new methods for `.Assay` and `.DimReduc`. Furthermore, they addressed issues in the integration of the code base by correcting neighbors and speeding up FindWeights. Lastly, they implemented helper functions and corrected spacing issues.
single-cell-genomicshuman-cell-atlassingle-cell-rna-seqcran
10XGenomics/scHLAcount
Jul 2019 - May 2021
Count HLA alleles in single-cell RNA-seq data
Contributions:24 commits, 1 PR, 10 pushes in 1 year 9 months
rna-seq
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