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.



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

Jihun Kim   🏸 decentralized optimization

Jaehyeon Jeong   🚴 parameter-free optimization


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!

(last updated
on Apr 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 as a POSTECH undergrad and/or have top grades.

We have various projects on optimization and its applications in machine learning. In particular, we are currently looking for students (including interns) to work on the following subjects: (1) optimization theory and algorithms in large-scale settings including decentralized optimization; (2) topics on large language models including their training, fine-tuning, compression, and multi-modality; (3) model optimization on commodity hardware; (4) interpretability of deep networks; and many more.


Please fill in this application form to apply for a position.