cv
Basics
| Name | Gyehun Go |
| rotation@kaist.ac.kr | |
| Url | https://hunrotation.github.io |
Education
-
2025.09 - Present Daejeon, South Korea
M.S. in Graduate School of Culture Technology
Korea Advanced Institute of Science and Technology (KAIST)
- Advisor: Juhan Nam
-
2021.03 - 2025.08 Seoul, South Korea
B.S. in Computer Science and Engineering
Seoul National University (SNU)
- Double Major in Statistics
- GPA: 3.90/4.3
Research experience
- 2025.03 - 2025.08
Music and Audio Computing Lab, KAIST
Research Intern
Advisor: Eunjin Choi, Prof. Juhan Nam- Developed AImoclips, a comprehensive benchmark for evaluating how well text-to-music (TTM) generation systems convey intended emotions to human listeners. The benchmark offers valuable insights into model-specific emotion rendering characteristics and supports future development of emotionally aligned TTM systems.
- 2024.06 - 2025.01
Department of Mathematics, UCLA
Research Intern
Advisor: Hyunsik Chae, Prof. Ernest Ryu- Developed AVSBench (Atomic Visual Skills Benchmark), a benchmark for evaluating visual understanding ability of visual language models(VLMs) by decomposing it into atomic visual skills. Found that VLMs struggle with most of these atomic visual skills that are obvious to humans.
- 2023.07 - 2023.08
Music and Audio Research Group, Seoul National University
Research Intern
Prof. Kyogu Lee- Implemented and tested Theme Transformer, a Transformer-based music generation framework conditioned on a small, thematic musical piece that generates symbolic music consistent with the theme.
- 2023.01 - 2023.06
Human-Computer Interaction Lab, Seoul National University
UROP(Undergraduate Research Opportunities Program) Student
Advisor: Hyeon Jeon, Prof. Jinwook Seo- Developed UMATO (Uniform Manifold Approximation with Two-phase Optimization), a novel dimension reduction algorithm for data visualization and evaluated its scalability.
Additional experience
- 2024.01 - 2024.06
AttentionX, an AI Research & Startup Group
3rd term member
- A member of a research team studying the evaluation of ambiguity resolution ability in large language models (LLMs), cooperating with Language & Knowledge Lab, KAIST
- Leader of a research team studying music editing methods using generative models
Skills
| Programming Languages | |
| Python | |
| C | |
| C++ | |
| Java | |
| R |
| Deep Learning | |
| PyTorch | |
| TensorFlow |
Languages
| Korean | |
| Native speaker |
| English | |
| Fluent |
| Japanese | |
| Intermediate |