Graduate Students

PhD Students

  • Hyungwon Choi (MS from KAIST in 2015)

    • Topic: image/video compression

  • Insu Han (MS from KAIST in 2017)

  • Yunhun Jang (MS from KAIST in 2015)

    • Topic: transfer learning

  • Hankook Lee (MS from KAIST in 2018)

    • Topic: anytime prediction, CNN architectures

  • Kimin Lee (MS from KAIST in 2015)

    • Topic: novelty detection, ensemble learning, adversarial examples, continual learning

    • Selected publication: ICML2017, ICLR2018, NIPS2018

  • Sangwoo Mo (MS from KAIST in 2018)

    • Topic: domain translation, adversarial learning

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

  • Junhyun Nam (BS from KAIST in 2017)

    • Topic: interpretable machine learning

  • Sejun Park (BS from KAIST in 2014, expected to graduate in Summer 2019)

    • Topic: belief propagation, markov chain monte carlo

    • Selected publication: UAI2015, AISTATS2017

  • Sukmin Yoo (BS from KAIST in 2017)

    • Topic: adversarial examples

MS Students

  • Jaehyung Kim (BS from KAIST in 2017)

    • Topic: image/video compression

  • Jongjin Park (BS from SNU in 2018)

    • Topic: transfer learning

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), Los Alamos National Laboratory

  • 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 Illinois at Urbana-Champaign

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

  • Adrain Weller (machine learning), University of Cambridge