J. Christopher Bare

• {middlename}{lastname} at gmail
• Wellington, New Zealand / Seattle, WA
• linkedin.com/in/j-christopher-bare
• github.com/cbare

Skills

Software engineer focused on data and machine learning.

• Skills: Python, SQL, Snowflake, AWS, Azure, Git, Bash, Docker, APIs, machine learning, data pipelines, CI/CD, automated testing, code review.
• Other experience: Keras, Tensorflow, scikit-learn, R, JavaScript, React, Redux, Java, Azure, Spark, Scala, Haskell, Clojure, Scheme, 6502 assembler.

Professional Experience

Data Engineer / Senior Data Engineer

Volpara Health – Wellington, New Zealand
Mar. 2021 - Present

• Built data platform for de-identified clinical data. Python, DICOM, Azure, Snowflake.
• Curated image datasets and annotations used to develop computer vision models for mammography.
• Prototyped image segmentation model to detect arterial calcification. PyTorch.

Senior Software Engineer

98point6 – Seattle, WA
Sept. 2019 - Aug. 2020

• Applied machine learning to on-demand text-based primary care medicine.
• MLOps for an NLP service for automated patient interview. Python, Flask, Keras, TensorFlow, scikit-learn, fastText, PostgreSQL, AWS.

Senior Software Engineer

Arivale – Seattle, WA
Feb. 2017 - May 2019

• Contributed to a health and wellness software platform integrating data from genetics, blood, microbiome, diet, and activity. Python, PostgreSQL, AWS, React.
• Worked with clinicians and researchers on a machine learning pipeline to make health recommendations based on lifestyle, genetics, and blood analytes. Python, pandas, scikit-learn, AWS.
• Maintained a pipeline that delivered a daily snapshot of cleaned, normalized, and batch-corrected data to researchers. R, data.table, Python, pandas, numpy, PostgreSQL, AWS.
• Built end-to-end system to collect medication and supplement usage classified by indication and mode of action. Python, R, PostgreSQL, AWS, React.

Senior Software Engineer

Sage Bionetworks – Seattle, WA
Aug. 2012 - Aug. 2016

• Developed client libraries for Synapse, a data sharing platform for collaborative scientific data analysis exposing a ReST API in Python and R.
• Developed code to manage predictive modeling and machine learning competitions on biomedical research questions as part of DREAM challenges. Python, R.
• Helped scientists apply version control, cloud computing, and Synapse to open and reproducible research.

Software Engineer

Institute for Systems Biology – Seattle, WA
Jun. 2006 - Jul. 2012

• Developed Network Portal, a database of gene regulatory networks. Python, Django, PostgreSQL, Solr, Javascript, jQuery, R.
• Created an interactive visualization of gene expression. Java, Swing, SQLite, R.
• Implemented Firegoose, a Firefox browser extension for data exchange between desktop and web applications. Javascript, Java, Web services, Microformats.

Prior experience

• Software development for applications in genomics, social media, e-commerce, pharmaceuticals, and biomedical research. Java, Swing, SQL, JavaScript.

Education

Continuing

Machine learning, deep learning, natural language processing, data engineering, and functional programming in Scala and Haskell.

M.S., Computer Science & Engineering

University of Washington – Seattle, WA
Jun. 2004 - Jun. 2007

B.S., Mathematical Science, Minor in Computer Science

Pennsylvania State University – University Park, PA
Jun. 1989 - Aug. 1992

Selected Publications

• The mPower study, Parkinson disease mobile data collected using ResearchKit. Bot et al., Nature Scientific Data, 2016.
• Prediction of human population responses to toxic compounds by a collaborative competition. Eduati et al., Nature Biotechnology, 2015.
• Simulation Studies as Designed Experiments: The Comparison of Penalized Regression Models in the “Large p, Small n” Setting. Neto et al., PLOS One, 2014.
• Global optimization of somatic variant identification in cancer genomes with a global community challenge. Boutros et al., Nature Genetics, 2014.
• Architecture for interoperable software in biology Bare et al., Briefings in bioinformatics, 2012
• Parallel evolution of transcriptome architecture during genome reorganization Yoon et al., Genome Research, 2011
• Integration and visualization of systems biology data in context of the genome Bare et al., BMC Bioinformatics, 2010
• Prevalence of transcription promoters within archaeal operons and coding sequences Koide et al., Molecular Systems Biology, 2009
• The Firegoose: two-way integration of diverse data from different bioinformatics web resources with desktop applications Bare et al., BMC Bioinformatics, 2007

More publications.

Last updated: October 2024.