Pi-chuan Chang
Software Engineer at Google
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolPi-chuan Chang is a seasoned software engineer and researcher with 11 years of experience building production ML and NLP systems at scale, currently leading Genomics efforts in Google Health (DeepVariant, DeepConsensus). He combines deep academic training (PhD in CS from Stanford) with hands-on engineering across backend, frontend, and distributed training pipelines, shipping work that has appeared in Nature Biotechnology. His background spans semantic parsing, personalization, and content relevance at Google and LinkedIn, and he has led product-driven research efforts at AltSchool integrating educator feedback into deployed tools. An active contributor to open-source genomics tooling, he helped optimize and harden the google/nucleus codebase for real-world performance. Pi-chuan is motivated by strong product vision and collaborative teams, favoring work that has measurable positive impact on users. He brings a rare blend of research rigor and pragmatic engineering leadership across both technical and cross-functional domains.
11 years of coding experience
8 years of employment as a software developer
Bachelor of Science, Computer Science, Bachelor of Science, Computer Science at National Taiwan UniversityDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Stanford University
English, Chinese, Mandarin
Github Skills (11)
file-handling10
file-processing10
genomics10
file-access10
python10
fileio10
testing9
cprogramming-language9
c-language9
data-structures8
data-structure8
Programming languages (5)
Github contributions (5)
google/nucleus
May 2018 - Nov 2021
Python and C++ code for reading and writing genomics data.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:28 commits, 10 comments, 8 issues in 3 years 6 months
Contributions summary:Pi-chuan primarily contributed to the improvement and maintenance of the nucleus codebase. They focused on refining error messages, enhancing utility functions for file pattern handling, and updating codebase headers. Moreover, the user addressed a performance optimization related to intersecting range sets. Their contributions also touched upon adding new features and refactoring code, ensuring the project's robustness.
genomics-databioinformaticspythongenomics
google/deepconsensus
Jul 2021 - Nov 2022
Contributions:2 releases, 1 review, 28 commits in 1 year 5 months
ccstransformerssequencecorrectconsensus
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