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NEWS

My paper "Model-Agnostic and Efficient Mixup Augmentation Guided by Saliency Maps" has been accepted at TPAMI, 2025.

Research Interest

  • Data Augmentation, Debiasing Representation
  • Data Inversion, Continual Learning
  • Reinforcement Learning for applying to real-world issues

Experience

  • 2021.01-2021.02 Research Intern, Department of Smart Data, AI Research Center, ETRI, Korea
  • 2021.03-2021.12 Research Intern, Center for Artificial Intelligence, KIST (Korea Institute of Science and Technology)
  • 2016.03-2022.02 Department of Electronic Engineering, Soongsil University, Korea (Bachelor degree, Summa Cum Laude)
  • 2022.03-2024.06 Student Researcher, Center for Artificial Intelligence, KIST (Korea Institute of Science and Technology)
  • 2022.03-2024.08 Master Candidate, Department of Artificial Intelligence, Korea University, Korea
  • 2024.09-present Hyundai Mobis

GitHub LinkedIn

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  1. GuidedMixup GuidedMixup Public

    Official PyTorch implementation of "GuidedMixup An Efficient Mixup Strategy Guided by Saliency Maps" (AAAI'23 Oral)

    Python 7 5

  2. rl-constraints-traffic rl-constraints-traffic Public

    Decentralized Deep Reinforcement Learning based Real-World Applicable Traffic Signal Optimization

    Python 11

  3. criminal-cargo-detection criminal-cargo-detection Public

    2021 한국 관세청 우범화물 탐지 경진대회 수상작 F1 51.0251 (1st prize)

    Jupyter Notebook 3

  4. flow_RL flow_RL Public

    Reinforcement Learning Practice for Multi and Single-Agent Autonomous vehicle

    Python 13 3

  5. DHP DHP Public

    Digital Health Hackathon 2021, Korea 수상작(1st prize)

    Python 2 2

  6. fabiano77/eswContest fabiano77/eswContest Public

    2020 임베디드SW경진대회 자율주행모형차부문 수상작

    C 4 2