My research goal is to develop computationally and data-efficient machine learning models and algorithms for real-world applications, grounded in meta-learning and meta-modeling. I am particularly interested in extending these approaches to natural language processing, self-supervised learning, dataset condensation, hyperparameter optimization, AI safety, privacy, and multi-modal learning.

Education

Ph.D. in Artificial Intelligence

2021 – Present
Korea Advanced Institute of Science and Technology

Advised by Sung Ju Hwang

M.S. in Artificial Intelligence

2019 – 2021
Korea Advanced Institute of Science and Technology

Advised by Sung Ju Hwang

B.S. in Computer Science

2012 – 2018
Korea University

Experiences

Research Intern

2025.07.01 - 2025.12.27
Microsoft Research Asia

Advised by Lei Song and Jiang Bian.

  • Multi-domain test-time scaling with reward models
  • Online data selection

Publications

  • Rethinking Reward Models for Multi-Domain Test-Time Scaling
  • Dong Bok Lee*, Seanie Lee*, Sangwoo Park, Minki Kang, Jinheon Baek, Dongki Kim, Dominik Wagner, Jiongdao Jin, Heejun Lee, Tobias Bocklet, Jinyu Wang, Jingjing Fu, Sung Ju Hwang, Jiang Bian, Lei Song
    arXiv 2025
  • Automated Structured Radiology Report Generation with Rich Clinical Context
  • Seongjae Kang, Dong Bok Lee*, Juho Jung, Dongseop Kim, Won Hwa Kim, Sunghoon Joo
    arXiv 2025
  • PCoreSet: Effective Active Learning through Knowledge Distillation from Vision-Language Models
  • Seongjae Kang, Dong Bok Lee*, Hyungjoon Jang, Sung Ju Hwang
    arXiv 2025
  • FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
  • Seanie Lee*, Sangwoo Park*, Dong Bok Lee*, Dominik Wagner, Haebin Seong, Tobias Bocklet, Juho Lee, Sung Ju Hwang
    NeurIPS 2025
  • Cost-Sensitive Freeze-Thaw Bayesian Optimization for Efficient Hyperparameter Tuning
  • Dong Bok Lee, Aoxuan Silvia Zhang*, Byungjoo Kim*, Junhyeon Park*, Steven Adriaensen, Juho Lee, Sung Ju Hwang, Hae Beom Lee
    NeurIPS 2025
  • Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks
  • Dongwoo Lee*, Dong Bok Lee*, Steven Adriaensen, Juho Lee, Sung Ju Hwang, Frank Hutter, Seon Joo Kim, Hae Beom Lee
    ICML 2025
  • SafeRoute: Adaptive Model Selection for Efficient and Accurate Safety Guardrails in Large Language Models
  • Seanie Lee*, Dong Bok Lee*, Dominik Wagner, Minki Kang, Haebin Seong, Tobias Bocklet, Juho Lee, Sung Ju Hwang
    ACL 2025 Findings
  • Dimensional Agnostic Neural Processes
  • Hyungi Lee, Chaeyun Jang, Dong Bok Lee, Juho Lee
    ICLR 2025
  • HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models
  • Seanie Lee*, Haebin Seong*, Dong Bok Lee, Minki Kang, Xiaoyin Chen, Dominik Wagner, Yoshua Bengio, Juho Lee, Sung Ju Hwang
    ICLR 2025
  • Self-Supervised Dataset Distillation for Transfer Learning
  • Dong Bok Lee*, Seanie Lee*, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang
    ICLR 2024
  • Self-Supervised Set Representation Learning for Unsupervised Meta-Learning
  • Dong Bok Lee*, Seanie Lee*, Kenji Kawaguchi, Yunji Kim, Jihwan Bang, Jung-Woo Ha, Sung Ju Hwang
    ICLR 2023
  • Dataset Condensation with Latent Space Knowledge Factorization and Sharing
  • Hae Beom Lee∗, Dong Bok Lee∗, Sung Ju Hwang
    arXiv 2022
  • Meta-StyleSpeech: Multi-Speaker Adaptive Text-to-Speech Generation
  • Dongchan Min, Dong Bok Lee, Eunho Yang, and Sung Ju Hwang
    ICML 2021
  • Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning
  • Dong Bok Lee, Dongchan Min, Seanie Lee, and Sung Ju Hwang
    ICLR 2021 (spotlight)
  • Contrastive Learning with Adversarial Perturbations for Conditional Text Generation
  • Seanie Lee*, Dong Bok Lee*, and Sung Ju Hwang
    ICLR 2021
  • Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction
  • Jinheon Baek, Dong Bok Lee, and Sung Ju Hwang
    NeurIPS 2020
  • Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs
  • Dong Bok Lee*, Seanie Lee*, Woo Tae Jeong, Donghwan Kim, and Sung Ju Hwang
    ACL 2020 (long papers)