Members

Alumni

Seungjae SHIN

PhD Alumni

KAIST E2-2, 4109

tmdwo0910@kaist.ac.kr

Research Interest

  • Data-Centric Generalization (e.g. Coreset Selection, Dataset Distillation, Domain Generalization, Active Learning)
  • ML Efficiency (e.g. Model Quantization, Coreset Selection)
  • ML Robustness (e.g. Debiasing, Fairness, Class-imbalance, Noisy Label Learning)
  • Representation Learning, Generative Model

Education

    Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea (Mar. 2020 ~)

  • Doctoral Degree Program in Industrial and Systems Engineering, AAILab
  • Academic Advisor: Professor Il-Chul Moon

    Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea (Mar. 2018 - Feb. 2020)

  • Master's Degree Program in Industrial and Systems Engineering, AAILab
  • Academic Advisor: Professor Il-Chul Moon

    Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea (Mar. 2013 - Feb. 2018)

  • Bachelor of Science in Industrial and Systems Engineering
    • Minor in Business and Technology Management

Publication

    International Conference

  • Seungjae Shin*, Heesun Bae*, Byeonghu Na, Yoon-Yeong Kim, Il-Chul Moon, Unknown Domain Inconsistency Minimization for Domain Generalization, International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024 
  • HeeSun Bae, Seungjae Shin, Byeonghu Na, Il-chul Moon, Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning, International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024 
  • Youngjae Cho, HeeSun Bae, Seungjae Shin, YeoDong Youn, Weonyoung Joo, Il-Chul Moon, Make Prompts Adaptable : Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior, AAAI Conference on Artificial Intelligence (AAAI 2024), Vancouver, Canada, Feb 22-25, 2024 
  • DongHyeok Shin*, Seungjae Shin*, Il-Chul Moon "Frequency domain-based Dataset Distillation", Conference on Neural Information Processing Systems (NeurIPS), 2023.
  • Seungjae Shin*, HeeSun Bae*, DongHyeok Shin, Weonyoung Joo, Il-Chul Moon "Loss Curvature Matching for Dataset Selection and Condensation", International Conference on Artificial Intelligence and Statistics (AISTATS) 2023
  • Seungjae Shin*, Heesun Bae*, Giwoon Kim, Youngsoon Cho, Dongwook Lee, Donggil Jeong, HyunJoon Kim, Hyunjung Lee, Hyungjun Moon, "Evaluation of Optimal Scene Time Interval for Out-of-hospital Cardiac Arrest using a Deep Neural Network", American Journal of Emergency Medicine
  • Seungjae Shin, Byeonghu Na, HeeSun Bae, JoonHo Jang, Hyemi Kim, Kyungwoo Song, Youngjae Cho, Il-Chul Moon "Improving Group-based Robustness and Calibration via Ordered Risk and Confidence Regularization", Workshop on Spurious Correlations, Invariance, and Stability on International Conference on Machine Learning (ICML-SCIS) 2022
  • HeeSun Bae*, Seungjae Shin*, Byeonghu Na, JoonHo Jang, Kyungwoo Song, Il-Chul Moon, "From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model", International Conference on Machine Learning (ICML 2022), Baltimore, Jul 17, 2022
  • Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-Chul Moon, "Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation", International Conference on Machine Learning (ICML 2022), Baltimore, Jul 17, 2022
  • Hyuck Lee, Seungjae Shin, Heeyoung Kim "ABC : Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning" Conference on Neural Information Processing Systems (NeurIPS), 2021.
  • Mingi Ji, Seungjae Shin, Seunghyun Hwang, Gibeom Park, Il-Chul Moon "Refine Myself by Teaching Myself : Feature Refinement via Self-Knowledge Distillation" IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  • Hyemi Kim, Seungjae Shin, JoonHo Jang, Kyungwoo Song, Weonyoung Joo, Wanmo Kang, Il-Chul Moon "Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder" AAAI Conference on Artificial Intelligence (AAAI) 2021.
  • Seungjae Shin, Kyungwoo Song, Joonho Jang, Hyemi Kim, Weonyoung Joo, and Il-Chul Moon “Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation” Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP) 2020.
  • Kyungwoo Song, JoonHo Jang, Seungjae Shin, and Il-Chul Moon “Bivariate Beta-LSTM” AAAI Conference on Artificial Intelligence (AAAI) 2020.
  • Joonho Jang, Seungjae Shin, Hyunjin Lee, Il-Chul Moon "Forecasting the Concentration of Particulate Matter in the Seoul Metropolitan Area Using a Gaussian Process Model" Sensors 2020
  • Yongjin Shin, Gihun Lee, Seungjae Shin, Se-young Yun, Il-Chul Moon "FEWER : Federated Weight Recovery" DistributedML'20: Proceedings of the 1st Workshop on Distributed Machine Learning

    Under-Review

  • Dongjun Kim, Kyungwoo Song, Seungjae Shin, Il-Chul Moon "Posterior-Aided Regularization for Likelihood-Free Inference"
  • Dongjun Kim, Weonyoung Joo, Seungjae Shin, Il-Chul Moon "Adversarial Likelihood-Free Inference on Black-Box Generator"
  • Weonyoung Joo, Dongjun Kim, Seungjae Shin, Il-Chul Moon "Generalized Gumbel-Softmax Gradient Estimator for Various Discrete Random Variables"

Award

  • Dean's list, KAIST, 2014
  • Honor student scholarship, KAIST, 2016
  • 1st Prize (대상), KAIST Invention Award, 2017
  • 최우수논문상, KSC2017 학부생 논문경진대회, 2017
  • 송현상, KAIST ISysE, 2018
  • Winner, Qualcomm Innovation Fellowship Korea, 2022
  • Winner, Qualcomm Innovation Fellowship Korea, 2023