Adelbert Chang
Senior Manager at NVIDIA
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolAdelbert Chang is a senior engineering leader in Seattle with 13 years of experience building cloud and AI platforms, currently leading teams at NVIDIA after directing cloud engineering at OctoAI. He combines hands-on functional programming expertise—contributing to notable open-source projects like Typelevel frameless, Cats, and Scalaz—with practical product delivery across startups and enterprises such as OctoML, Target, and Box. His work on frameless and Cats shows deep competence in Scala type systems and data-frame abstractions that bridge research-grade ideas to production data pipelines. Known for moving between principal engineering and management roles, he excels at scaling platform teams while retaining technical ownership of core systems. Trained in creative studies with a computer science emphasis from UCSB, he brings a designer’s sensibility to complex engineering problems. Colleagues describe him as a pragmatic engineer-leader who surfaces non-obvious architecture improvements while keeping teams focused on measurable outcomes.
13 years of coding experience
12 years of employment as a software developer
B.S., Creative Studies (Computer Science Emphasis), B.S., Creative Studies (Computer Science Emphasis) at University of California, Santa Barbara
English, Chinese
Stackoverflow
7,260reputation
537kreached
54answers
69questions
scala
top-5%
traits
top-5%
Github Skills (28)
spark10
lib10
futures10
scalaz10
scala10
f10
functional-programming10
shapeless10
documentation10
concurrency10
data-structure9
hlist9
functor9
dataframe9
serialization9
Programming languages (19)
Github contributions (5)
typelevel/frameless
Mar 2015 - Jan 2019
Expressive types for Spark.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 releases, 87 commits, 40 PRs in 3 years 9 months
Contributions summary:Adelbert primarily contributed to the core functionality of the `frameless` library, which targets expressive types for Spark. Their work focused on defining and implementing the `DataSheet` class, providing core DataFrame combinators with HList support, and enabling the conversion between Row and HList structures. Additionally, the user implemented the `DataColumn` class and performed several refactorings and improvements to the overall library.
functional-programmingspark-mlexpressivesparkscala
typelevel/cats
Feb 2015 - Dec 2017
Lightweight, modular, and extensible library for functional programming.
Role in this project:Back-end Developer
Back-end DeveloperContributions:326 commits, 257 PRs, 144 pushes in 2 years 10 months
Contributions summary:Adelbert primarily contributed to the `cats` library, focusing on adding documentation, links to relevant papers, and improving serializability of the codebase. The changes included modifying core type classes like `Traverse`, `Monad`, `Applicative`, and `Foldable` to add more comments and include links to papers for better documentation. They also annotated types and fixed issues related to serialization, ensuring the library's compatibility and usability.
functional-programmingtagless-finalscalamodularextensible
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