Wonseok Hwang
Assistant Professor at University of Seoul-서울시립대학교
Seongnam-si, South Korea
Summary
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Senior🎓
Top SchoolWonseok Hwang is an Assistant Professor and machine learning researcher with a decade of experience bridging NLP, Legal AI, and biophysics through probabilistic and deep learning methods. He has a strong publication record in top AI venues (EMNLP, ACL, NeurIPS, AAAI, ECCV) and applies statistical physics and variational Bayesian approaches to sequential and multimodal data. His industry experience includes research engineering at NAVER and contributions to notable open-source projects such as naver/sqlova, where he improved data pipelines and deterministic behavior in ML workflows. He combines hands-on ML engineering with theoretical modeling, having moved from single-molecule biophysics and optics to semantic parsing and document information extraction. Based in Seongnam-si, South Korea, he leverages interdisciplinary training from a PhD in Biophysics to tackle practical problems in Legal NLP and scientific data analysis. Notably, his background in mesoscopic stochastic modeling often informs principled solutions to noisy, real-world ML tasks.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Biophysics, Doctor of Philosophy - PhD, Biophysics at Seoul National University
Github Skills (9)
pytorch10
machine-learning10
debug10
nlp10
python10
modeling9
trainings9
data-preprocessing9
tensorflow7
Programming languages (5)
Github contributions (5)
naver/sqlova
Jan 2019 - Dec 2019
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 26 commits, 11 PRs in 10 months
Contributions summary:Wonseok primarily contributed to bug fixes and improvements within a machine learning project. These involved addressing deterministic pseudo-random number generation issues, where-column ordering problems, and other minor code corrections. They also made modifications to data loading and preprocessing steps, suggesting involvement in the data pipeline of the machine learning workflow. The user also worked on adding new functions.
lbox-kr/lbox-open
Mar 2022 - Dec 2022
Contributions:2 releases, 47 commits, 19 PRs in 9 months
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