Minseon Kim

github google scholar linked in linked in CV

About

Me!

Welcome to my page! :)
I am a Ph.D. student in MLAI Lab, advised by Professor Sung Ju Hwang at KAIST. If you are interested in my research or bio, feel free to contact me. This is my CV!

Education

Ph.D. in Artificial Intelligence

  • Korea Advanced Institute of Science and Technology (KAIST), 2020-present
  • Advisor: Prof. Sung Ju Hwang

M.S. in Electrical Engineering

  • Korea Advanced Institute of Science and Technology (KAIST), 2018-2020
  • Thesis: Differential representation of face pareidolia in human and deep neural network

B.S. in Bio & Brain Engineering and Computer Science (double major)

  • Korea Advanced Institute of Science and Technology (KAIST), 2013-2018

Publication

(C: Conference, J: Journal, P: Preprint, W: Workshop, A: Abstract only conference)
[C5] Meta-Prediction Model for Distillation-aware NAS on Unseen Datasets
       Hayeon Lee*, Sohyun An*, Minseon Kim, Sung Ju Hwang
        International Conference on Learning Representations, 2023, Spotlight PDF Code

[C4/W2] Rethinking the Entropy of Instance in Adversarial Training
       Minseon Kim, Jihoon Tack, Jinwoo Shin, Sung Ju Hwang
       First IEEE Conference on Secure and Trustworthy Machine Learning, 2023, ICML AdvML workshop, 2021 PDF Code

[P3/W5] Targeted Adversarial Self-Supervised Learning
       Minseon Kim, Hyeonjeong Ha, Sooel Son, Sung Ju Hwang
        NeurIPS SafetyML workshop, 2022 PDF

[P2/W4] Few-shot Transferable Robust Representation Learning via Bilevel Attacks
       Minseon Kim*, Hyeonjeong Ha*, Sung Ju Hwang
        NeurIPS SafetyML workshop, 2022 PDF (*equal contribution)

[P1] Language Detoxification with Attribute-Discriminative Latent Space
       Minseon Kim*, Jin Myung Kwak*, Sung Ju Hwang
       Preprint, 2022 PDF (*equal contribution)

[W3] Lightweight Neural Architecture Search with Parameter Remapping and Knowledge Distillation
       Hayeon Lee*, Sohyun An*, Minseon Kim, Sung Ju Hwang
       AutoML workshop, 2022 PDF (*equal contribution)

[C3/W1] Consistency Regularization for Adversarial Robustness
       Jihoon Tack, Sihyun Yu, Jongheon Jeong, Minseon Kim, Sung Ju Hwang, and Jinwoo Shin
       ICML AdvML workshop Oral presentation (2021), AAAI (2022) PDF Code

[C2] Adversarial Self-Supervised Contrastive Learning
       Minseon Kim, Jihoon Tack, Sungju Hwang
       Conference on Neural Information Processing Systems, NeurIPS 2020 PDF Code

[C1] Progressive Face Super-Resolution via Attention to Facial Landmark
       Deokyun Kim*, Minseon Kim*, Gihyun Kwon*, Daeshik Kim
       BMVC (2019) PDF Code (*equal contribution)

[J1] MRI-based classification of neuropsychiatric systemic lupus erythematosus patients with self-supervised contrastive learning
       Francesca Inglese* and Minseon Kim* et al. (Correspond to Itamar Ronen)
       Frontiers in Neuroscience (Impact Factor: 4.67) PDF (*equal contribution)

[A2] Minseon Kim et al., MRI-based classification of neuropsychiatric systemic lupus erythematosus patients with self-supervised contrastive learning, ESMRMB 2020, (abstract only)
[A1] Minseon Kim et al., T1 Image Synthesis with Deep Convolutional Generative Adversarial Networks, Organization for Human Brain Mapping 2018 (abstract only)

Work Experience

Internship (06.2019-08.2019)
Radiology Department, Leiden University Medical Center (LUMC), Leiden, Netherland

Presented Talk


Invited talk "Adversarial Self-Supervised Contrastive Learning"
  • Stella Yu's Group, UC Berkeley, Virtual, Nov 2020.
  • NeurIPS Social: ML in Korea, Virtual, Dec 2020.
  • Korea Software Congress (KSC): Korea Post-NeurIPS-2020 Workshop, Virtual, Dec 2020.
  • Kakao Brain, Virtual, Feb 2021.
  • Korean Conference on Computer Vision, Virtual, Aug 2021.
Lightening talk "MRI-based classification of neuropsychiatric systemic lupus erythematosus patients with self-supervised contrastive learning"
  • ESMRMB, virtual, Sep 2020
General talk
  • "Deep neural network from CNN to GAN", LUMC, Leiden, Netherland, 2019 (2 weeks)

Academic Activity

Conference reviewer
  • International Conference on Learning Representations (ICLR): 2022
  • International Conference on Machine Learning (ICML): 2021, 2022
  • Conference on Neural Information Processing Systems (NeurIPS): 2021, 2022
  • Association for Computational Linguistics (ACL) ARR: December, 2022
  • Association for the Advancement of Artificial Intelligence (AAAI): 2020, 2021
  • Asian Conference on Machine Learning (ACML): 2020, 2021
Journal reviewer
  • Transactions on Machine Learning Research
  • Neural Computing and Applications
  • Asian Conference on Machine Learning Journal Track (ACML)
Area chair
  • The AAAI 2023 Workshop on Representation learning for Responsible Human-Centric AI: 2023 (Top Area Chair)

Contact

minseonkim@kaist(dot)ac(dot)kr