Jialin Ding
Assistant Professor at Princeton University
United States
Summary
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Senior🎓
Top SchoolJialin Ding is an Assistant Professor at Princeton CS and an applied researcher with 11 years of experience bridging systems research and production ML at institutions including MIT (PhD), Stanford, Microsoft, and AWS. His work spans learned data structures and high-performance systems—evidenced by contributions to the widely referenced microsoft/ALEX in-memory Adaptive Learned indEX where he improved build infrastructure, core components, and benchmarking. At AWS he progressed from Applied Scientist to Senior Applied Scientist and Amazon Scholar, translating research prototypes into scalable services. He combines deep academic training with hands-on engineering across C++ codebases and cloud platforms, and brings a knack for improving code quality and performance in foundational data systems.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Massachusetts Institute of TechnologyBachelor of Science (BS) Electrical Engineering, Bachelor of Science (BS) Electrical Engineering at Stanford University
Stackoverflow
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Github Skills (9)
algorithm10
data-structures10
algorithms10
c-language10
cmake10
cprogramming-language10
data-structure10
benchmark9
benchmarking9
Programming languages (9)
Github contributions (5)
microsoft/ALEX
Apr 2020 - Aug 2021
A library for building an in-memory, Adaptive Learned indEX
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 46 commits, 10 PRs in 1 year 4 months
Contributions summary:Jialin's contributions center around the development and maintenance of the `alex` library, which is an in-memory, Adaptive Learned indEX. They implemented the initial CMakeLists.txt to establish the build process, and they fixed compiler warnings, indicating a focus on code quality and maintainability. Furthermore, the user made several modifications to the core components of the library, including data node and alex structures, and also added a simple benchmark. This suggests the user's contributions were focused on improving the performance and the overall functionality of the library.
memoryindexlearnedadaptivemachine-learning
jialinding/jialinding.github.io
May 2018 - Nov 2024
Contributions:28 pushes, 1 branch in 6 years 6 months
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