Jeongho Park
Deception Island, Antarctica, Republic Of Korea
Summary
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SeniorJeongho Park is an applied scientist who translates 13+ years of cognitive neuroscience expertise into practical, data-driven solutions at the intersection of human perception and AI. Based in Cambridge, he has led multidisciplinary teams at Harvard and now designs large-scale perception experiments at Adobe to evaluate AI performance in video and editing tools. His strengths combine experimental design, advanced quantitative methods, and compelling visual analytics to convert complex behavioral and neural data into strategic insights for product and research teams. He has a track record of building novel experimental hardware and VR environments for fMRI studies and generating human-vision benchmarks that informed new computer vision models. Comfortable with Python, R, MATLAB and SQL, he’s particularly interested in quantitative UX research and applying multi-armed bandit thinking—hinted by his “MAB player” GitHub bio—to optimize human-centered evaluation frameworks.
11 years of coding experienceProgramming languages (3)
Github contributions (5)
jeongho/ray
Jun 2022 - Jul 2026
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Contributions:10 pushes in 4 years 1 month
apirayscalabledistributed-applicationshyperparameter
jeongho/timefold-quickstarts
Jun 2023 - Nov 2025
Planning optimization made easy. Get started with Timefold Solver here.
Contributions:1 PR, 124 pushes, 10 branches in 2 years 5 months
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