MAJEPPA: Morphing and Assessing in a Unified Piano Performance Space
ISMIR 2026 · Conference paper · To appear
Best Paper Award nomination
Music Information Retrieval · Generative AI for Music
I work on music information retrieval and generative music, focusing on performance representation and expressive generation. I study relationships between scores and piano performances, including timing, dynamics, and variation across levels of expertise. My work also explores Nanyin ensemble generation, using pipa-centric data and graph representations to model heterophony and ornamentation. Across these projects, I investigate music tokenization, latent-space interpolation, and timbre-based interfaces for creative interaction. I studied music at Quanzhou Normal University (MA, 2023–2026), supervised by Prof. Jianbing Xiahou.

ISMIR 2026 · Conference paper · To appear
Best Paper Award nomination
CSMT 2025 · 12th National Conference on Sound and Music Technology · Conference paper
ISMIR 2025 · Late-breaking / demo
LLM4Music Workshop at ISMIR 2025 · Workshop poster
3rd Workshop on Human-Centric Music Information Research at ISMIR 2025 · Workshop paper
New in ML Workshop at ICML 2025 · Workshop poster
A Visual Journey Through MIR Algorithms
An interactive performance system that uses MIR algorithms as a compositional mechanism. Spiral trajectories navigate timbre spaces, while a visual interface reveals algorithmic states and sonic transformations.
Real-time MFCC analysis · k-NN interpolation · Granular synthesis · Archimedean, logarithmic, and Fermat spiral trajectories
RenCon 2025: Expressive Piano Performance Rendering Contest
An expressive piano rendering system that models phrasing, dynamics, and timing from symbolic scores. Its renderings were played on a Yamaha Disklavier in the RenCon 2025 live concert, where listeners rated anonymized performances and tried to identify the human reference.
Symbolic score-to-performance rendering · Learned phrasing, dynamics, and timing