Minseon Kim

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Me!

I am a final year Ph.D. student in MLAI Lab, advised by Professor Sung Ju Hwang at KAIST.
My primary research interests lie in the development of robust representations across a variety of domains and tasks, including image classification, language generation, and neural architecture search. Recently, I am interested in how to learn robust representation in the multi-modality and in the foundation models. If you're interested in collaborating on research projects related to robust representation, feel free to contact me :) This is my CV!

Publication (*equal contribution)

Automatic Jailbreaking of the Text-to-Image Generative AI Systems
       Minseon Kim, Hyomin Lee, Boqing Gong, Huishuai Zhang, Sung Ju Hwang
        ICML Next Generation of AI Safety Workshop 2024, PDF Project Page

Protein Representation Learning by Capturing Protein Sequence-Structure-Function Relationship
       Eunji Ko*, Seul Lee*, Minseon Kim*, Dongki Kim, Sung Ju Hwang
        ICLR MLGenX workshop 2024 (Spotlight), PDF

Effective Targeted Attacks for Adversarial Self-Supervised Learning
       Minseon Kim, Hyeonjeong Ha, Sooel Son, Sung Ju Hwang
        NeurIPS 2023, PDF Code

Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations
        Hyeonjeong Ha*, Minseon Kim*, Sung Ju Hwang
        NeurIPS 2023, PDF Code

Language Detoxification with Attribute-Discriminative Latent Space
       Minseon Kim*, Jin Myung Kwak*, Sung Ju Hwang
        ACL 2023, PDF

Context-dependent Instruction Tuning for Dialogue Response Generation
       Jin Myung Kwak, Minseon Kim, Sung Ju Hwang
        ArXiv 2023, PDF

Meta-Prediction Model for Distillation-aware NAS on Unseen Datasets
       Hayeon Lee*, Sohyun An*, Minseon Kim, Sung Ju Hwang
        ICLR 2023 (Spotlight), PDF Code

Rethinking the Entropy of Instance in Adversarial Training
       Minseon Kim, Jihoon Tack, Jinwoo Shin, Sung Ju Hwang
        IEEE SaTML 2023, PDF Code

Lightweight Neural Architecture Search with Parameter Remapping and Knowledge Distillation
       Hayeon Lee*, Sohyun An*, Minseon Kim, Sung Ju Hwang
       AutoML workshop 2022, PDF

Learning Transferable Adversarial Robust Representations via Multi-view Consistency
       Minseon Kim*, Hyeonjeong Ha*, Dong Bok Lee, Sung Ju Hwang
        NeurIPS SafetyML workshop 2022, Under review, PDF

Consistency Regularization for Adversarial Robustness
       Jihoon Tack, Sihyun Yu, Jongheon Jeong, Minseon Kim, Sung Ju Hwang, and Jinwoo Shin
       AAAI 2022, PDF Code

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 2022 (Impact Factor: 4.67), PDF

Adversarial Self-Supervised Contrastive Learning
       Minseon Kim, Jihoon Tack, Sungju Hwang
        NeurIPS 2020, PDF Code

Progressive Face Super-Resolution via Attention to Facial Landmark
       Deokyun Kim*, Minseon Kim*, Gihyun Kwon*, Daeshik Kim
        BMVC 2019, PDF Code

MRI-based classification of neuropsychiatric systemic lupus erythematosus patients with self-supervised contrastive learning
       M. Kim, F. Inglese, G. Steup-Beekman, T. Huizinga, M. Van Buchem, J. Bresser, D. Kim, I. Ronen
       ESMRMB 2020

T1 Image Synthesis with Deep Convolutional Generative Adversarial Networks
       Minseon Kim, Chihye Han, Jisuk Park, Dae-Shik Kim
       OHBM 2018

Experience

Research Internship (06.2024-08.2024)
ERA–KASL AI Safety Research, University of Oxford

Research Collaboration (07.2023-05.2024)
Theory Center, Microsoft Research Asia, Collaborate with Prof. Huishuai Zhang

Research Internship (06.2019-08.2019)
Radiology Department, Leiden University Medical Center (LUMC), Collaborate with Prof. Itamar Ronen

Presented Talk


Invited talk
"Automatic Jailbreaking of the Text-to-Image Generative AI Systems"
  • Guest Lecture, Korea University, May. 2024
"Effective Targeted Attacks for Adversarial Self-Supervised Learning"
  • Samsung AI Forum 2023, Samsung, Nov. 2023
"Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations"
  • R&D AI Conference, Hyundai, Nov. 2023
"Adversarial Self-Supervised Contrastive Learning"
  • Stella Yu's Group, UC Berkeley, Nov. 2020
  • NeurIPS Social: ML in Korea, Dec. 2020
  • Korea Software Congress (KSC): Korea Post-NeurIPS-2020 Workshop, Dec. 2020
  • Kakao Brain, Feb. 2021
  • Korean Conference on Computer Vision, Aug. 2021
"MRI-based classification of neuropsychiatric systemic lupus erythematosus patients with self-supervised contrastive learning"
  • ESMRMB (Lightening Talk), Sep. 2020
"Deep neural network from CNN to GAN"
  • LUMC, Aug. 2019

Academic Activity

Conference reviewer
  • International Conference on Learning Representations (ICLR): 2022-2024
  • International Conference on Machine Learning (ICML): 2021-2024
  • Conference on Neural Information Processing Systems (NeurIPS): 2021-2023
  • Association for Computational Linguistics (ACL) ARR: 2022-2023
  • Association for the Advancement of Artificial Intelligence (AAAI): 2020-2021
  • AAAI Safe, Robust and Responsible AI (SRRAI): 2023
  • Asian Conference on Machine Learning (ACML): 2020-2021
Journal reviewer
  • IEEE Transactions on Neural Networks and Learning Systems
  • Neural Computing and Applications
  • Machine Learning
  • Transactions on Machine Learning Research
  • Asian Conference on Machine Learning Journal Track
Area chair
  • The AAAI 2023 Workshop on Representation learning for Responsible Human-Centric AI: 2023 (Top Area Chair)
Organizer

Education

Ph.D. in Artificial Intelligence (current)

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

M.S. in Electrical Engineering

  • Korea Advanced Institute of Science and Technology (KAIST)
  • 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)

Contact

minseonkim@kaist(dot)ac(dot)kr