Kevin Wang

PHD Student at Brown University

Providence, Rhode Island, United States
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Summary

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Rockstar
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Top School
Kevin Wang is a PhD student in Computer Science at Brown University with 12 years of software engineering experience spanning industry and research. He spent a year as an AI Resident at Meta FAIR researching computational game theory and has contributed backend logic and test automation to high-profile open-source projects like DeepMind's OpenSpiel. Kevin blends rigorous academic training with practical engineering—fixing game implementations, adding solver functionality, and strengthening unit tests to improve algorithm correctness. Past roles include full-stack and engineering positions at startups and companies such as Shift and Square, giving him product-focused delivery experience. Based in Providence, he pairs a research-driven mindset with a knack for shipping reliable, well-tested systems. On a lighter note, he’s a big Taylor Swift fan and quotes Rutherford on scientific skepticism, hinting at both curiosity and humor.
code12 years of coding experience
job2 years of employment as a software developer
bookDoctor of Philosophy - PhD, compoter sceince, Doctor of Philosophy - PhD, compoter sceince at Brown University
bookUniversity of California, Irvine
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Github Skills (13)

coregames10
unit-testing10
python10
reinforcement-learning10
videogames10
testing10
algorithms9
data-structure9
cprogramming-language9
multi-agent9
c-language9
algorithm9
data-structures9

Programming languages (10)

TypeScriptLiquidC++JavaScriptHaskellHTMLXSLTJupyter Notebook

Github contributions (5)

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google-deepmind/open_spiel

Jan 2021 - Sep 2022

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
Role in this project:
userBack-end Developer & Test Automation Engineer
Contributions:6 reviews, 17 commits, 21 PRs in 1 year 8 months
Contributions summary:Kevin primarily contributed to the backend logic and testing of the OpenSpiel framework. They fixed bugs in existing game implementations, such as Tic-Tac-Toe and Oshi-Zumo, and updated test files to reflect those changes. The user also added functionalities like `tabular_average_policy()` to CFRPlusSolver and added testing for repeated games' utility sum, demonstrating a focus on algorithm improvements and code quality through testing. Furthermore, they modified the Universal Poker game to ensure correctness and added unit tests.
cppmultiagentgamespythondatamining
VitamintK/voteforwang

Mar 2015 - Feb 2019

Contributions:31 pushes, 2 branches in 4 years
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