About Me

I am a second-year M.S./Ph.D. student majoring in Computer Science and Engineering at Seoul National University, advised by Prof. U Kang. I received my B.S. in Computer Science from KAIST.

My research engages deeply with data mining and machine learning, specializing in the study of graph neural networks and model compression.

Contact Info.

• Email : minjun.kim [at] snu.ac.kr (Preferred)
• Address : 6th Floor, Bldg. 303, 1 Gwanak-ro, Gwanak-gu, Seoul, South Korea
• External Links : [ Homepage | Google Scholar | LinkedIn | DBLP | Github | ORCID | Calendar | CV (pdf) ]

Education

• Seoul National University (Mar. 2024 - Current)
  M.S./Ph.D. Student in Computer Science and Engineering
  Advisor: Prof. U Kang


• KAIST (Feb. 2019 - Feb. 2024)
  B.S. in Computer Science
  (Double Major: Business and Technology Management)

Publications

Conference Papers

• [C4] Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models
  
  Seungcheol Park, Jeongin Bae, Beomseok Kwon, Minjun Kim, Byeongwook Kim, Se Jung Kwon, U Kang^†, and Dongsoo Lee
  ACL 2025 (The 63rd Annual Meeting of the Association for Computational Linguistics), Vienna, Austria
  [ Paper | Code | OpenReview | arXiv | BibTeX ]


• [C3] Zero-shot Quantization: A Comprehensive Survey
  
  Minjun Kim*, Jaehyeon Choi*, Jongkeun Lee, Wonjin Cho, and U Kang^†
  IJCAI 2025 (The 34th International Joint Conference on Artificial Intelligence), Montréal, Canada
  Survey Track
  [ Paper | Paper List | arXiv | BibTeX ]


• [C2] AugWard: Augmentation-Aware Representation Learning for Accurate Graph Classification
  
  Minjun Kim, Jaehyeon Choi, SeungJoo Lee, Jinhong Jung^†, and U Kang^†
  PAKDD 2025 (The 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining), Sydney, Australia
  Oral Presentation
  [ Paper | Code | arXiv | BibTeX ]


• [C1] SynQ: Accurate Zero-shot Quantization by Synthesis-aware Fine-tuning
  
  Minjun Kim, Jongjin Kim, and U Kang^†
  ICLR 2025 (The Thirteenth International Conference on Learning Representations), Singapore
  [ Paper | Code | Poster | OpenReview | ICLR Virtual | BibTeX ]

Patents

• Method and Apparatus for Accurate Zero-Shot Quantization by Synthesis-Aware Fine-Tuning
  Minjun Kim, Jongjin Kim, and U Kang
  Filed 23th May, 2025
• Graph Classification Method and Apparatus based on Augmentation-Aware Representation Learning
  Minjun Kim, Jaehyeon Choi, SeungJoo Lee, Jinhong Jung, and U Kang
  Filed 30th Oct., 2024

Awards and Honors

• PAKDD Student Travel Award for attending PAKDD 2025 (Mar. 2025)
  
• Youlchon AI Research Fellowship (Sep. 2024)
  

Projects

• AI Platform @ Samsung Electronics (May. 2024 - Current)
  
  "Mixed Precision Quantization of Large Language Models for On-Device Execution"
  Mixed Precision Quantization of LLMs and MLLMs


• SW-StarLab @ IITP (Jun. 2023 - Current)
  
  "Model Compression for Deep Neural Networks"
  Few-shot and Zero-shot Quantization of Vision Task Models


• AI Research Project @ Youlchon Foundation (Jun. 2023 - Current)
  
  "Advancing Language Models Through Compression of Large Language Models"
  Model Compression of LLMs

Academic Services

Reviewer

• IJCAI 2025

Teaching Assistant

• Data Structure (M1522.000900) @ Seoul National University (Spring 2025)
  
• Data Mining (M1522.001400) @ Seoul National University (Fall 2024)
  
• Machine Learning Course @ HD Hyundai Heavy Industries (Summer 2024)
  
• Advanced Data Scientists Course @ LG Electronics (Winter 2024)
  
• AI Boosting Camp @ Hyundai Motor Group (Fall 2023, Spring 2024, Summer 2025)