About Me

I am currently an undergraduate student studying Artificial Intelligence at the School of Future Technology, South China University of Technology. I am advised by Prof. Qi Liu on music generation and machine learning.

I also work closely with Music X Lab, where I am guided by Prof. Gus Xia and Dr. Ziyu Wang.

Research Interest

The primary goal of my research is to develop effective representations for symbolic music that balance structural preservation with encoding efficiency. I believe that effective representation is the foundation for tackling various downstream tasks in symbolic music, from understanding to generation.

To address this challenge, I integrate methods from computer vision and natural language processing to design a novel symbolic music representation. Currently, my method has achieved promising results on piano datasets, demonstrating the potential of this cross-modal strategy. I aim to refine this approach and validate it across diverse instruments and applications, working toward a state-of-the-art representation framework for symbolic music.

Our work on this approach has been submitted to ICASSP 2026. Feel free to check out our demo page for more details!