Runzhong Wang - Postdoctoral Associate

Runzhong Wang

Postdoctoral Associate

Cambridge, Massachusetts, United States

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Summary

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Rockstar

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Top School

Runzhong Wang is a Postdoctoral Associate at MIT with nine years of experience spanning research software engineering, machine learning for combinatorial optimization, and MLOps. He earned his PhD and BE from Shanghai Jiao Tong University and now works in the Coley Group applying practical engineering to deep graph matching and optimization research. His open-source contributions include back-end development and maintenance for Thinklab-SJTU projects—extending a popular ML-for-CO paper generator to support new problem types and implementing efficient computational primitives like CSXMatrix3d. Comfortable bridging research and production, he focuses on robust implementations, reproducible workflows, and clear documentation. Colleagues value his knack for translating complex algorithms into maintainable code and tooling that accelerates research.

9 years of coding experience

Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Shanghai Jiao Tong University

Chinese, English

Github Skills (14)

pytorch10

combinatorial-optimization10

python10

file-access7

fileio7

file-handling7

file-processing7

sphinx6

dockers5

data-structure5

docker5

algorithms5

algorithm5

data-structures5

Programming languages (7)

C++CSCSSGoJupyter NotebookPythonCuda

Github contributions (5)

Thinklab-SJTU/ThinkMatch

Sep 2019 - Nov 2022

A research protocol for deep graph matching.

Role in this project:

Back-end Developer & MLOps Engineer

Contributions:3 releases, 79 commits, 8 PRs in 3 years 3 months

Contributions summary:Runzhong primarily contributed to the core functionality of the project, fixing bugs, adding new features, and refactoring existing code. They worked on the implementation of the `CSXMatrix3d` class and other utility functions, which suggests a focus on the computational aspects of the graph matching problem. The commits also demonstrate an involvement in setting up and updating the documentation of the project, including installation guides.

graphgraph-matchingneural-graph-matchingquadratic-assignment-problemcombinatorial-optimization

Thinklab-SJTU/awesome-ml4co

Mar 2021 - Dec 2022

Awesome machine learning for combinatorial optimization papers.

Role in this project:

Back-end Developer

Contributions:27 commits, 4 PRs, 15 pushes in 1 year 8 months

Contributions summary:Runzhong primarily focused on enhancing the `src/generator.py` file within the repository. Their commits involved adding support for different combinatorial optimization problems (QAP, JSSP, and others) by modifying the code to incorporate new problem types and abbreviations. They also made formatting improvements and merged branches, indicating maintenance and integration efforts on the paper list generator.

combinatorial-optimizationmachine-learningoperations-researchpaper-list

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