Sung Kim
Co-Founder, CEO at Upstage
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSung Kim is a serial AI entrepreneur and former academic with 11 years of experience building teams and products that put advanced machine learning into real-world use. As Co-Founder and CEO of Upstage in San Francisco he leads efforts to make "AI Packs for Everyone," after scaling Clova AI at NAVER/LINE from a team of 3 to 150 and shipping products used by hundreds of millions. He combines deep research roots—PhD in Computer Science and postdoctoral work at MIT/CSAIL—with hands-on ML engineering, contributing tutorials and implementations for TensorFlow and PyTorch that help teach others (notably the widely used DeepLearningZeroToAll series). His background in reliable systems is reflected in test-driven contributions to RNN projects and in improving documentation to lower the barrier for contributors. Known for bridging academia and product teams, he often translates state-of-the-art models into production-ready code and educational resources.
11 years of coding experience
16 years of employment as a software developer
University of California Santa Cruz
Github Skills (32)
unit-testing10
markdown10
pytorch10
word2vec10
python10
testing10
user-manual10
machine-learning10
rnn-model10
recurrent-neural-networks10
n10
linear-regression10
mask-rcnn10
keras10
deep-learning10
Programming languages (15)
Github contributions (5)
hunkim/DeepLearningZeroToAll
Feb 2017 - Dec 2019
TensorFlow Basic Tutorial Labs
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:183 commits, 107 PRs, 223 pushes in 2 years 9 months
Contributions summary:Sung contributed significantly to the project by adding and modifying Keras-based deep learning labs, demonstrating a focus on TensorFlow and related technologies. Their work involved implementing various machine learning models, including linear and logistic regression, within the context of the TensorFlow framework. Furthermore, the user adapted data loading mechanisms (e.g., from CSV files), and incorporated backpropagation techniques within their solutions. These modifications suggest an active role in building and refining the machine learning components of the project.
tensorflowkerasmxnetpytorchpython
hunkim/PyTorchZeroToAll
Oct 2017 - Nov 2020
Simple PyTorch Tutorials Zero to ALL!
Role in this project:ML Engineer
ML EngineerContributions:89 commits, 12 PRs, 80 pushes in 3 years 1 month
Contributions summary:Sung contributed to the project by implementing and demonstrating various PyTorch tutorials, ranging from basic linear regression and auto-gradient examples to logistic regression and CNN models for MNIST. The contributions included the initial setup of code and slides, followed by changes to filenames. Furthermore, the user finished up to Lec 9 and added inception and basic RNN examples. The user is working on creating tutorials for various machine learning and deep learning techniques.
pytorchpython
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