Chanran Kim
Summary
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SeniorChanran Kim is a senior Developer Relations leader and generative AI researcher based in Seoul with 9 years of experience spanning developer advocacy, applied research, and open-source contributions. Currently a Senior Developer Relations Manager at NVIDIA and founder of the non-profit PseudoLab ML community, he blends community-building with hands-on work in multimodal generative models and time-series forecasting. His engineering background includes production ML systems, synthetic dataset pipelines using Unity/Unreal, and deploying microservices, while his open-source contribution to facebook/prophet shows practical expertise adapting holiday logic for Korean lunar calendars. Chanran has represented global brands like HP and NVIDIA as a data science ambassador and speaks internationally, reflecting a rare mix of technical depth, developer empathy, and cross-cultural communication. He holds advanced studies in computer software and a dual background in physics and computer engineering, which informs his interdisciplinary approach to AI problems.
10 years of coding experience
Stackoverflow
449reputation
29kreached
21answers
0questions
Github Skills (16)
forecasting10
forecast10
time-series10
python10
data-analysis10
machine-learning8
r8
notebook7
ubuntu6
heroku6
moving-average6
werkzeug6
sliding-window6
aws-cloud6
conditional-statements6
Programming languages (10)
Github contributions (5)
facebook/prophet
Jul 2019 - Jun 2020
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Role in this project:
Data Scientist
Data ScientistContributions:5 commits, 3 PRs, 6 comments in 11 months
Contributions summary:Chanran primarily contributed to the `hdays.py` file, focusing on the addition and subsequent removal of Korean holiday data. These changes involved integrating specific logic for determining holiday dates based on the Lunar calendar. Further, they updated a notebook file to reflect the changes, indicating an understanding of the project's documentation and user-facing materials. Their work demonstrates an understanding of time series data and holiday effects within the context of the Prophet forecasting tool.
time-seriesforecastingrpython
AI-Trolls/python-komsu
Dec 2018 - Mar 2019
Contributions:55 commits, 48 pushes, 1 branch in 2 months
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