Chris Donahue


(Update) I am graduating soon and seeking a full-time position (CV).

I am currently a PhD candidate in computer music at UC San Diego. I am jointly advised by Miller Puckette (music) and Julian McAuley (computer science). My primary research goal is to make music easier to play and understand using machine learning.

In 2013, I received a BS in computer science from the Turing Scholars Program at the University of Texas at Austin. In 2016, I received an MA in computer music from UCSD.

Selected Publications

Work Experience

Media Coverage

  • Business Insider A Google intern helped build an AI tool inspired by 'Guitar Hero' to let rookies play piano
  • The Verge Google’s AI-powered Piano Genie lets anyone improvise perfectly by bashing buttons
  • Evening Standard Piano Genie: Google's AI programme is like Guitar Hero for the piano world
  • Engadget Google’s Piano Genie lets anyone improvise classical music

  • MIT Tech Review Machine-Learning Algorithm Watches DDR, Then Creates Dances of Its Own
  • The Verge Scientists have taught a neural network to choreograph Dance Dance Revolution levels
  • The Register Yet another job menaced by AI! Uh, wait, it says here... Dance Dance Revolution designers
  • Vice This Machine Learned to Choreograph by Watching Dance Dance Revolution


  • (2018) Transcribe a batch of solo piano recordings to MIDI (link)
  • (2017) PhD qualifying examination (pdf)
  • (2016) Master's thesis (pdf)
  • (2015) Prototype for MOOC on computer music fundamentals using Web Audio API (link)
  • (2015) Mobile-friendly, networked musical controller (demo)
  • (2014) Multichannel convolution reverb plugin (screenshot, code, windows vst)
  • (2013) OpenGL 3D spectrogram (page, code)
  • (2012-2014) Played keyboard for Food Group

Last updated 2018/12/27