Computer Science Researcher

I have obtained my Ph.D. in Computer Science and Engineering at Seoul National University, advised by Hyun Oh Song. I previously graduated from Seoul National University in 2018 with a B.S. in electrical and computer engineering.

My research interest is efficient combinatorial optimization with deep learning algorithms. I handled several combinatorial optimization problems including energy minimization problems and QCQP in several domains: Hashing, disentanglement, and network lightweighting. I'm confident in formulating optimization problems and solve with efficient algorithm design.

Recent News

I served as a technical research personnel in Seoul National University (2021-2024).

Yeonwoo Jeong

Publications

AISTATS 2022 research visualization

Optimal channel selection with discrete QCQP

Yeonwoo Jeong, Deokjae Lee, Gaon An, Changyong Son, Hyun Oh Song

International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

CVPR 2019 cascading optimization visualization

End-to-End Efficient Representation Learning via Cascading Combinatorial Optimization

Yeonwoo Jeong, Yoonsung Kim, Hyun Oh Song

IEEE Computer Vision and Pattern Recognition (CVPR), 2019

ICML 2019 disentanglement visualization

Learning Discrete and Continuous Factors of Data via Alternating Disentanglement

Yeonwoo Jeong, Hyun Oh Song

International Conference on Machine Learning (ICML), 2019

EMI exploration algorithm visualization

EMI: Exploration with Mutual Information

Hyoungseok Kim, Jaekyeom Kim, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song

International Conference on Machine Learning (ICML), 2019

Long talk (159/3424=4.6%)

ICML 2018 quantizable representations

Efficient end-to-end learning for quantizable representations

Yeonwoo Jeong, Hyun Oh Song

International Conference on Machine Learning (ICML), 2018

Long talk (213/2473=8.6%)

Honors & Awards

Yulchon AI Star Fellowship

2021

Qualcomm Innovation Fellowship (South Korea) Winner

2020

NRF Global Ph.D. Fellowship Program

2019

KFAS Computer Science Graduate Student Scholarship

2018

Coding Skills

Python100%
C++70%
Java50%
Rust30%