Hi, I am Jongyun

Summary:

Hi, I’m Jongyoon Shin. After completing my Bachelor’s degree in Electrical and Electronic Engineering at Kookmin University, I am currently pursuing a Master’s degree in Computer Science with a focus on Artificial Intelligence at the same university. My research interests lie in Parameter Efficient Fine-Tuning (PEFT), Meta-Learning, Unlearning, and Model Compression, with a particular focus on efficiently utilizing large AI models and applying them to real-world problems. I am passionate about creating innovative value through new discoveries, and I aspire to contribute to bringing meaningful changes through AI by researching cutting-edge technology trends and exploring creative approaches.

🎓 Education

• M.Sc., Artificial Intelligence, Department of Computer Science and Engineering

  Kookmin University (Mar 2023 - Feb 2025)

• B.Sc., Department of Electrical and Electronic Engineering

  Kookmin University (Mar 2017 - Aug 2022)

  • Overall GPA: 4.22/4.5
  • Major GPA: 4.39/4.5

📜 Publications

International Conferences

1. J. Shin, S. Han, and J. Kim, “Cooperative meta-learning with gradient augmentation,” in Uncertainty in Artificial Intelligence (UAI - acceptance rate of 27%). PMLR, 2024 [paper] [code]

2. J. Shin, S. An, and J. Kim, “ESFP: Effective Soft Prompt Fine-Tuning using Parameter-efficient Mixture-of-Experts,” in the International Conference on Machine Learning (ICML), 2025 (Under Review)

3. J. Shin, H. Lee, and J. Kim, “Context-based prompt tuning for pretrained language model via test-time adaptation,” in the Uncertainty in Artificial Intelligence (UAI), 2025 (Under Review)

4. J. Shin, J. Kim, and J. Kim, “Entropy-guided meta-initialization regularization for few-shot text classification,” in ACM International Conference on Web Search and Data Mining (WSDM), 2025 (Under Review)

5. H. Cho, J. Shin, and J. Kim, “Quantized Contrastive Unlearning,” in The Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (Under Review)

6. J. Kim, J. Shin, and J. Kim, “Exploring Diverse Sparse Network Structures via Dynamic pruning with Weight Alignment,” in Uncertainty in Artificial Intelligence (UAI), 2025 (Under Review)

7. D. Lee, J. Shin, and J. Kim, “Weight initialization based on gradient similarity for versatile machine unlearning,” in The Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (Under Review)

International Journal

1. S. An, J. Shin, and J. Kim, “Quantization-aware training with dynamic and static pruning,” in Institute of Electrical and Electronics Engineers (IEEE Access), 2024 (Under Review)

🏆 Awards

• Outstanding Talent Award (M.Sc.) in Computer Science 🏆, Kookmin University (Feb 2025)

• Best Graduate Student Thesis-Based IP Creation Award 🏆, Kookmin University (Aug 2024)

• International Collegiate EV Autonomous Driving Competition 🥇, International e-Mobility Expo, World Council for e-Mobility (May 2024)

• Outstanding Graduate Award, Department of Electronic Engineering 🥇, Kookmin University (Aug 2022)

• Kookmin University Achievement Award 🏆, Kookmin University (Aug 2022)

• Autonomous Video Object Detection Contest 🥇, Ministry of Trade, Industry and Energy & Korea Automotive Research Institute (Dec 2021)

📞 Contact

Name	Jongyun Shin
E-mail	jjongyn@gmail.com
LinkedIn	Visit Page