My research focuses on data-driven music visualization that supports students and teachers. For example, augmented and alternative sheet music notation(opens in new tab) helps reading and understanding a piece more quickly. Collecting and visualizing practice data(opens in new tab) supports musicians in learning their instruments more efficiently. Besides audio and MIDI, such practice data may include motion capture(opens in new tab) of the musician. To make analysis more immersive and increase the visual connection to the instrument, visualization can be displayed in virtual(opens in new tab) and augmented reality(opens in new tab). My collaborations include work on visualization for human-AI composing(opens in new tab) and participating in the DR4ET hackathon(opens in new tab).