Michael Lin is a founder and CEO with 15 years of engineering experience building and scaling backend systems and AI products, currently helping businesses accelerate ROI from AI through software development, audits, and tailored training. He combines big-tech leadership at Netflix and Amazon—where he led a multi-year re-architecture powering billions of notifications and architected services for the Amazon Dash Button—with hands-on engineering expertise in genome informatics and systems software. A UC Berkeley EECS graduate, Michael is a pragmatic engineer-founder who emphasizes rapid prototyping and robust implementation, reflected in his contributions to high-profile open-source projects like RocksDB and vg where he improved reliability and error handling. Based in Honolulu, he differentiates his consultancy by applying an engineering-first approach and a custom discovery methodology that validates prompts and prototypes before full builds.
16 years of coding experience
6 years of employment as a software developer
S.B. M.Eng., S.B. M.Eng. at Massachusetts Institute of Technology
Specifications of SAM/BAM and related high-throughput sequencing file formats
Role in this project:
Frontend Developer
Contributions:1 review, 20 commits, 33 PRs in 4 years 2 months
Contributions summary:Mike primarily worked on updating the `htsget_interop.html` file within the repository. Their contributions focused on refining the user interface of the webpage, including modifying the layout, adding a copy button, and incorporating links to the source code. They also updated the style sheet and data endpoints.
Contributions:37 commits, 13 PRs, 83 pushes in 1 year 9 months
Contributions summary:Mike primarily focused on improving error handling and robustness within the `vg` genome variation graph tools. Their contributions include tightening error detection in index metadata operations, implementing error handling for protobuf operations, and rewriting the parallel processing of data streams. They also addressed file input validation and ensured that non-existent files caused failures. These changes indicate a focus on improving the reliability and stability of the tools.
genomegenome-graphdnagenomicsbioinformatics
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