Current Members


PhD Students

  • Insu Han (BS, MS from KAIST in 2017)

    • Topic: large-scale machine learning, spectral methods, stochastic gradient descent, graph neural networks

    • First-authored publication: ICML2015, ICML2017, SISC2017, NIPS2018

  • Jaehyung Kim (BS, MS from KAIST in 2019)

    • Topic: regularization methods, large-margin training

  • Hankook Lee (BS, MS from KAIST in 2018)

    • Topic: meta learning, transfer learning, unsupervised learning

    • First-authored publication: arXiv2018, ICML2019

  • Kimin Lee (BS, MS from KAIST in 2015)

  • Sangwoo Mo (BS from POSTECH in 2016, MS from KAIST in 2018)

    • Topic: generative models, adversarial learning, active learning

    • First-authored publication: ICLR2019

PhD+MS Integrated Students

  • Sungsoo Ahn (BS from KAIST in 2015)

  • Jongheon Jeong (BS from KAIST in 2017)

    • Topic: network compression, CNN architectures, automated machine learning, adversarial examples

    • First-authored publication: ICML2019

  • Junhyun Nam (BS from KAIST in 2017)

    • Topic: interpretable machine learning

  • Sejun Park (BS from KAIST in 2014)

  • Seokmin Youn (BS from KAIST in 2017)

    • Topic: adversarial examples

MS Students

  • Seungjoon Moon (BS from KAIST in 2019)

    • Topic: natural language processing

  • Jongjin Park (BS from SNU in 2018)

    • Topic: transfer learning, generative models

  • Jihoon Tak (BS from KAIST in 2019)

    • Topic: reinforcement learning

BS Students

  • Junho Han

  • Junsoo Kim

  • Seunghyun Lee


  • Eunjoo Yoon (

Past Students

  • Donggyu Yun (PhD 2016, co-advised by Prof. Yung Yi, rightarrowNAVER)

  • Sanghyuk Jun (MS 2016, rightarrowKAKAOrightarrowNAVER CLOVA AI Research)

  • Jungseul Ok (PhD 2016, co-advised by Prof. Yung Yi, rightarrowKTHrightarrowUIUC)

  • Kwihyuk Jin (MS 2017, rightarrowQualcomm USA)

  • Hyeryung Jang (PhD 2017, co-advised by Prof. Yung Yi, rightarrowKing's College London)

  • Tae-Hyun Oh (PhD 2017, co-advised by Prof. In So Kweon, rightarrowMIT)

  • Donggyu Lee (MS 2018)

External Collaborators

We acknowledge many great collaborators out of KAIST who have influenced us through their expertises on various disciplines.

  • Haim Avron (numerical computing), Tel Aviv University

  • Michael Chertkov (statistical physics), University of Arizona

  • Minsu Cho (computer vision), Pohang University of Science and Technology

  • Bohyung Han (computer vision), Seoul National University

  • Honglak Lee (deep learning), University of Michigan

  • Dmitry Malioutov (machine learning), T. J. Watson IBM Research Center

  • Sewoong Oh (machine learning), University of Washington

  • Eric Vigoda (theoretical computer science), Georgia Institute of Technology

  • Adrian Weller (machine learning), University of Cambridge and The Alan Turing Institute