Matthew Rocklin
Human at Coiled Computing
Austin, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolMatthew Rocklin is a seasoned software leader and CEO of Coiled with 15 years of experience building scalable Python infrastructure for data science and distributed computing. He is the original author and principal maintainer behind Dask, and has driven production-ready integrations across Kubernetes, cloud object stores (s3fs/gcsfs), and storage formats (fastparquet, zarr), combining deep systems knowledge with developer experience. Previously he led system software efforts at NVIDIA and coordinated ecosystem-wide work at Anaconda, reflecting a rare mix of research pedigree (PhD, University of Chicago) and operational leadership. His open-source contributions span performance-sensitive libraries (cuDF, cloudpickle, bcolz) and tooling for real-time and sparse data, emphasizing robustness, testing, and maintainability. Based in Austin, he also writes thoughtfully about professional life, and brings a practical focus on making large-scale cloud compute delightful for Python users.
15 years of coding experience
8 years of employment as a software developer
BA, Physics, Mathematics, Astronomy, BA, Physics, Mathematics, Astronomy at University of California, BerkeleyDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of Chicago
Stackoverflow
56,481reputation
6.5mreached
1,171answers
200questions
pandas
top-1%
dataframe
top-5%
foreach
top-1%
sympy
top-5%
java
top-5%
numpy
top-1%
Github Skills (126)
data-stream10
google-cloud-platform10
package-management10
python10
sympy10
testing10
bash10
refactor10
distributed-computing10
gcp10
scheduling10
mat10
infrastructure10
parallel-computing10
file-processing10
Programming languages (27)
Github contributions (5)
dask/dask
Jan 2015 - Jul 2026
Parallel computing with task scheduling
Role in this project:
Back-end Developer
Back-end DeveloperContributions:196 reviews, 2809 PRs, 1992 pushes in 11 years 8 months
Contributions summary:Matthew's commits primarily focus on enhancing Dask's handling of file I/O and data processing operations. They made several improvements related to Parquet file reading and writing, including adding support for schema inference, filter pushdown, and various engine optimizations. Furthermore, the commits reflect efforts to streamline the implementation of core functionalities like range-based and index-based access methods, as well as the refactoring of data processing methods. The user also added a new method for efficiently accessing and handling data within partitions.
parallel-computingdaskpythonpydatanumpy
blaze/odo
Nov 2014 - Jun 2015
Data Migration for the Blaze Project
Role in this project:Back-end Developer
Back-end DeveloperContributions:853 commits, 94 PRs, 129 pushes in 6 months
Contributions summary:Matthew primarily focused on enhancing data migration functionalities within the Blaze Project's data migration framework. Their work involved implementing and refining data conversion routines, including the addition of a regex dispatcher, creating temporary storage mechanisms, and improving the conversion of different data types between various libraries and containers. Furthermore, the user worked to improve the handling of missing and inconsistent data types, and to support the inclusion of HDFS files.
data-migration
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