Bo Kim
Research Team Lead at Kakao Corp
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolBo Kim is a research team lead at Kakao with 10 years of experience building and applying machine learning and deep learning across industry and research labs. He completed a master's at Korea University focusing on text mining and machine learning, and has recently been deepening expertise in image-domain deep learning. Prior roles at KakaoBrain, NAVER, LG Electronics and KT reflect a track record of moving models from research to product contexts in Korea’s top tech organizations. An active practitioner in sequence models, his open-source contributions include implementing RNN/LSTM and attention-based sequence-to-sequence workflows in the well-known "Deep Learning Zero to All" TensorFlow repo. He combines strong academic results (top grades in industrial engineering) with hands-on engineering, mentoring teams while still coding and experimenting with novel architectures. Based in Seoul, he describes himself as a self-motivated deep learning engineer who bridges rigorous research and production impact.
10 years of coding experience
4 years of employment as a software developer
석사과정, 산업경영공학, 4.5 / 4.5, 석사과정, 산업경영공학, 4.5 / 4.5 at 고려대학교경제학 학사, 응용통계학, 4.2/4.5, 경제학 학사, 응용통계학, 4.2/4.5 at Konkuk University
English
Github Skills (6)
keras10
machine-learning10
lstm10
rnn-model10
tensorflow10
n10
Programming languages (9)
Github contributions (5)
deeplearningzerotoall/TensorFlow
Oct 2018 - Mar 2019
Deep Learning Zero to All - Tensorflow
Role in this project:
ML Engineer
ML EngineerContributions:108 commits, 89 pushes, 2 comments in 5 months
Contributions summary:Bo's commits primarily involve modifications to an iPython Notebook focused on sequence-to-sequence learning. The changes include the implementation of various RNN architectures such as SimpleRNN, StackedRNN and LSTM, along with code incorporating various techniques such as padding, masking and one-hot encoding, sequence loss, and the generation of predicted labels. Further, the user has implemented Sequence-to-Sequence training with attention.
deep-learningtensorflow
lassl/lassl
Nov 2021 - Nov 2022
LASSL: LAnguage Self-Supervised Learning
Contributions:30 reviews, 26 commits, 7 PRs in 11 months
self-supervised-learning
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.