Lee Optimization Group
We pursue research in machine learning and optimization. To this end, we develop theories and algorithms using computational and mathematical tools. Our ultimate goal is to provide robust and provable solutions to challenging problems in artificial intelligence, particularly those in large-scale settings. We are passionate about translating our findings into practical applications that can benefit society.
Members
Administrator
Dami So
Graduate students
Jinseok Chung
🏃
dual based optimization
Donghyun Oh
🏀
parameter-free optimization
Sungbin Shin
🎧
model optimization
Dahun Shin
🎬
second-order optimization
Dongyeop Lee
🎹
dual based optimization
Seonghwan Park
🎙
zeroth-order optimization
Jueun Mun
🥊
decentralized optimization
Jaehyeon Jeong
🚴
parameter-free optimization
Jihun Kim
🏸
decentralized optimization
Yongjun Kim
🏋
zeroth-order optimization
Kwanhee Lee
🎸
model optimization
Stories
We also spend time together on various occasions (see gallery for more).
Join us
We are always on the lookout for talented and motivated students to join us!
Openings
(last updated
on Jul 2024)
We have a few open positions for graduate students for the upcoming terms; candidates are expected to have strong computational and mathematical skills. We also have internship positions for those who are enrolled at POSTECH or have top grades elsewhere.
We have various projects on optimization and its applications in machine learning. In particular, we are currently looking for students to work on (1) optimization in distributed settings; (2) large language models for their training, fine-tuning, continual learning, and multi-modality; (3) model optimization on commodity hardware; (4) interpretability of deep networks.
Application
Please fill in this application form to apply for a position.
Acknowledgements
Our research is generously supported by multiple organizations including government agencies (NRF, IITP), industry (Google, Samsung, Naver, Intel), and academic institutions (POSTECH, Yonsei).