Yijun Chen
Software Engineer at Jane Street
Pittsburgh, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolYijun Chen is a software engineer with nine years of experience and dual majors in Information Systems and Computer Science from Carnegie Mellon University, currently working at Jane Street. He has hands-on experience across trading tech and developer advocacy, having moved from a quantitative trading internship to a full-time engineering role while earlier building developer portals and ML-backed pricing models at TigerGraph. An active open-source contributor, he implemented NumPy-compatible operators in Apache MXNet, enhancing its NumPy API support for a widely used deep learning framework. He also has blockchain research experience, shipping smart contracts for a community currency project, demonstrating a blend of practical engineering and economic thinking. Based in Pittsburgh, Yijun combines low-level numerical work with product-facing developer tools and a knack for turning research prototypes into production-ready systems.
9 years of coding experience
1 year of employment as a software developer
Shenzhen Middle SchoolBachelor of Science - BS Information Systems, Bachelor of Science - BS Information Systems at Carnegie Mellon University
Github Skills (12)
mxnet10
tensor10
tensorflow10
python10
numpy10
api-design9
apidoc9
cprogramming-language9
c-language9
api9
deep-learning8
machine-learning8
Programming languages (7)
Github contributions (5)
apache/mxnet
Apr 2020 - Aug 2020
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Role in this project:
Back-end Developer
Back-end DeveloperContributions:9 commits, 11 PRs, 58 comments in 4 months
Contributions summary:Yijun primarily contributed to the implementation of NumPy operations within the MXNet framework. Their commits focused on adding support for various NumPy functions like `rollaxis`, `tril_indices`, and `fill_diagonal`. These changes involved modifying core files related to NumPy operator implementations, including shape and type inference, and the implementation of both forward and backward passes. The user's work expanded the feature set of MXNet's NumPy integration, enhancing its compatibility with the NumPy API.
pythonschedulerdataflowmutationdata-science
SaltyFishWithJava/JavaRushHour
Dec 2016 - Oct 2017
Contributions:12 commits, 11 pushes, 1 branch in 11 months
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