Ping Wang王平

I am an undergraduate in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where I am advised by Prof. Noah A. Smith in Noah’s ARK. Since May 2026, I have also been a student researcher in the Music and AI Lab at National Taiwan University, advised by Prof. Yi-Hsuan Yang.

My research focuses on making generative models more controllable, adaptive, and aligned with human intentions. I am particularly interested in post-training, reinforcement learning, and multimodal learning: how models can learn from feedback, how to design meaningful reward signals, and how models can adapt through interaction. I am also interested in how these ideas extend to multi-agent systems, where agents must coordinate and respond to one another in dynamic environments.

Much of my recent work explores these questions through music and audio, including rubric-based optimization for text-to-music generation, human-aligned evaluation of music transcription, and audio-to-symbolic music understanding. Through these projects, I aim to develop methods that improve how generative models learn, understand, and interact with complex information, with applications both within and beyond music.

I'm always happy to chat about research, music, or possible collaborations. The best way to reach me is by email at pingw220@gmail.com.