Hi, this is Ethan.

My legal name is Yuqiang Li.

Ethan's selfie

Iโ€™m a symbolic music AI researcher with 4 yearsโ€™ experience integrating domain knowledge into deep learning. I specialise in multi-task learning, feature engineering, and evaluation of music generation.

I also build interactive web tools for visualising and analysing music, art, and computer science, using p5.js and WebMIDI to advance creative approaches in symbolic music AI.

My Tools

A realtime MIDI visualiser.


Forget the old piano roll—this is a tonal palette. Every note bursts with colour, living in its own tonal context.


Play and see how the musical tonalities tell a story.

Different notes drawn as circles

Sometimes our typos can exhibit habitual patterns.


This tool analyses the speed and accuracy of your typing in bigrams.

This is simply a musical note book.


Play the chord, release it, and it shows up on the notebook

Different notes drawn as circles
Different notes drawn as circles

A nearly exhaustive list of all the chords and their occurrences in differnt scales.

A realtime MIDI chord visualiser.


Don't know what chord you are playing? Just Chord will tell.


(This is an earlier version of the Chord Typer above but it has a grand staff view)

Why are there 12 pitch classes? They are generated from the perfect fifths.

Publications

Yuqiang Li, Shengchen Li and George Fazekas
The 16th International Symposium on Computer Music Multidisciplinary Research (CMMR), 2023
Yuqiang Li, Shengchen Li and George Fazekas
23rd International Society for Music Information Retrieval Conference (ISMIR), 2022