Junyoung Park
Research Scientist
Sunnyvale, California, United States
Summary
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SeniorJunyoung Park is a Senior Machine Learning Researcher with nine years of experience and a PhD from KAIST, specializing in (deep) learning for dynamic networked systems and decision-making. He has led industrial collaborations across telecommunications, semiconductor manufacturing, and robotics, producing 15+ publications and deploying deep-learning services in production. At Qualcomm he focuses on optimizing LLM inference, and previously built AI solvers for combinatorial optimization at a startup (Omelet). A practiced educator, he’s delivered corporate courses and hands-on GNN/RL tutorials for Samsung, LG, SK, and others, and has experience applying learned controllers and neural combinatorial methods to real-world processes. Colleagues describe him as a researcher who bridges rigorous theory and practical deployment, often translating meta-learning and GNN advances into industry-ready optimization tools.
9 years of coding experience
Github Skills (68)
benchmark10
segment10
hydra10
vehicle-routing-problem10
operations-research10
attention-model10
combinatorial-optimization10
scatter10
pytorch10
pytorch-lightning10
ai9
audio9
python9
deep-learning9
graph-convolutional-networks9
Programming languages (3)
Github contributions (5)
Junyoungpark/CGS
Jun 2021 - Feb 2022
The official implementation of Convergent Graph Solvers (CGS)
Contributions:16 commits, 9 pushes in 8 months
graphpytorchgraph-neural-networksgnn-model
Junyoungpark/GTMARL-SC2ENV
Nov 2019 - Dec 2019
2019 Fall - Game theory and Multi-agent RL Termproject
Contributions:38 commits, 1 PR, 32 pushes in 26 days
multi-agent
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