CV

Curriculum Vitae of Hyukjin Kim.

Contact Information

Name Hyukjin Kim
Professional Title M.S. Candidate · Computer Vision
Email ekaterina9@yonsei.ac.kr
Phone +82 010.8621.4609

Professional Summary

M.S. candidate at the Computer Vision Lab, Yonsei University. Research interests include open-vocabulary object detection, vision-language models, and multimodal learning. B.S. in Electrical & Electronic Engineering from Yonsei University.

Education

  • 2025 - Present

    Seoul, Republic of Korea

    M.S.
    Yonsei University
    Computer Vision Lab
    • Advised by Prof. Bumsub Ham. Research on open-vocabulary object detection, vision-language models, and multimodal learning.
  • 2023 - 2025

    Seoul, Republic of Korea

    B.S.
    Yonsei University
    Electrical & Electronic Engineering
    • GPA 3.80 / 4.30.
    • Graduation research on open-vocabulary object detection — EE-Festival Most Popular Award (3rd place).
  • 2019 - 2023

    Incheon, Republic of Korea

    B.S. (transferred)
    Inha University
    Electrical Engineering
    • GPA 4.10 / 4.50. Transferred to Yonsei University in 2023.

Awards

  • 2024
    Most Popular Award (3rd place)
    EE-Festival, Yonsei University

    For graduation research on improving open-vocabulary object detection.

  • 2024
    Academic Excellence Award
    Yonsei University

    For academic performance in the 2023 Fall semester.

  • 2023
    Outstanding Study-Group Team
    Yonsei University
  • 2022
    Academic Excellence Award
    Inha University

    For academic performance in the 2022 Spring semester.

  • 2019
    Academic Excellence Award
    Inha University

    For academic performance in the 2019 Spring semester.

Projects

  • Improving Open-Vocabulary Object Detection via Knowledge Distillation

    Graduation Research (with Junghyun Park) · Yonsei University · 🏆 EE-Festival Most Popular Award (3rd place).

    • Built on the BARON baseline; identified its limitations and applied knowledge distillation to surpass baseline performance.
  • Self-Supervised Image Classification with SwAV

    Deep Learning, Final Project · Yonsei University.

    • Online clustering with the Sinkhorn–Knopp algorithm on a ResNet-18 backbone; transferred a pretext-trained network to CIFAR-100 classification.
  • Deep Learning Lab — 12 Implementation Projects

    Deep Learning · Yonsei University.

    • VGG/ResNet, Spatial Transformer Network, FSRCNN, FCN, RetinaNet (Focal Loss), Grad-CAM, neural style transfer, DCGAN, CycleGAN, Seq2Seq with attention, network quantization, and self-supervised learning (SwAV).
  • Foundations of AI — ML Algorithms from Scratch

    Introduction to AI · Yonsei University.

    • Lasso/Ridge regression, Decision Tree and AdaBoost, and modular neural networks — implemented without ML libraries.

Skills

Programming (Advanced): Python, PyTorch, NumPy, Git, Linux
Deep Learning (Advanced): Object Detection, Vision-Language Models, Generative Models, Self-Supervised Learning

Languages

Korean : Native speaker
English : TOEIC 895

Interests

Research interests: Person ReID, Multimodal Learning, Vision-Language Models, Open-Vocabulary Object Detection, Deep Learning