Timothy Danford
Software Engineer at INFLECTION Medicine
Cambridge, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolTimothy Danford is a software engineer with 15 years of experience building cloud-native genomics and data-processing platforms, currently working at Inflection Medicine in Cambridge. He has led architecture and engineering efforts across industry and research—most recently as a Software Architect at Novartis NIBR—and combines production-grade systems design with deep domain knowledge in genomics. As a founding engineer at Genome Bridge he helped prototype distributed read-processing and variant query pipelines using Apache Spark and Parquet, and contributed bug fixes and schema enhancements to the well-known ADAM genomics project. Timothy’s background spans hands-on field engineering, application architecture, and prototyping consent-matching and data-discovery tools, reflecting an ability to bridge research requirements and scalable product implementations. He holds an MIT PhD in Computer Science and often brings research-grade rigor to pragmatic engineering problems.
15 years of coding experience
23 years of employment as a software developer
PhD Computer Science, PhD Computer Science at Massachusetts Institute of TechnologyB.A. Computer Science, B.A. Computer Science at Dartmouth College
Github Skills (9)
scala10
parquet10
bioinformatics10
genomics10
spark10
data-processing10
java9
javas9
avro9
Programming languages (6)
Github contributions (5)
bigdatagenomics/adam
Nov 2013 - Mar 2015
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:71 commits, 5 PRs, 2 pushes in 1 year 3 months
Contributions summary:Timothy primarily contributed to fixing bugs and improving the codebase by addressing typos, missing brackets, and incorrect data loading. They focused on the `adam-commands` module, modifying files related to variant calling and loading SAM files, demonstrating expertise in genomics data processing. They also added new functionality to sequence dictionary extraction and handling, which includes improving the ADAMRecord schema. These changes suggest a focus on improving data loading and processing within the genomics analysis platform.
pythonbioinformaticsadamlicensedbig-data
broadinstitute/adam
Nov 2013 - Aug 2014
Contributions:88 commits in 9 months
avrolicensedfile-formatparquetapache
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