Peter Landwehr is a veteran data scientist, data engineer, and research software engineer with 11 years of experience building analytics pipelines and production-ready tooling for biomedical and social science applications. Based in San Francisco, he has driven sepsis detection research at Cytovale—designing feature extraction workflows, interactive Jupyter tools, and scalable ingestion scripts that bridge on-prem TrueNAS and Amazon S3 storage—while also maintaining research compute clusters. His background spans applied research at Carnegie Mellon on social media and disaster response, industry work on DARPA-scale web data analytics, and hands-on DevOps automation for prominent open-source infrastructure like conda-forge. Peter blends rigorous academic training (Carnegie Mellon, Princeton) with pragmatic engineering: he teaches teams best practices in Python, git, and data munging and has a knack for turning messy, multimodal data (video, clinical records, and streaming extracts) into auditable, reproducible analyses.
11 years of coding experience
18 years of employment as a software developer
Doctor of Philosophy (Ph.D.) (Proposed) Computation Organizations and Society, Doctor of Philosophy (Ph.D.) (Proposed) Computation Organizations and Society at Carnegie Mellon University
Bachelor of Arts (A.B.) Computer Science, Bachelor of Arts (A.B.) Computer Science at Princeton University
A place to submit conda recipes before they become fully fledged conda-forge feedstocks
Contributions:239 pushes, 197 branches in 7 years 2 months
placeconda-forgerecipescondapython
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