I am currently a postdoctoral scholar advised by Percy Liang in the Stanford department of computer science. Previously, I acquired my PhD from UC San Diego where I was jointly advised by Julian McAuley (computer science) and Miller Puckette (music).
My research sits at the intersection of machine learning, music, audio, and interaction. My primary goal is to build powerful generative models for different types of multimedia that can be used intuitively by humans to augment creative capacity.
- Enabling Language Models to Fill in the Blanks In ACL, 2020.
- LakhNES: Improving Multi-instrumental Music Generation with Cross-domain Pre-training In ISMIR, 2019.
- Expediting TTS Synthesis with Adversarial Vocoding In INTERSPEECH (oral), 2019. * Equal contribution
- Piano Genie In ACM IUI, 2019.
- Adversarial Audio Synthesis In ICLR, 2019.
- GANSynth: Adversarial Neural Audio Synthesis In ICLR, 2019.
- The NES Music Database: A Multi-instrumental Dataset with Expressive Performance Attributes In ISMIR, 2018.
- Semantically Decomposing the Latent Spaces of Generative Adversarial Networks In ICLR, 2018.
- Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition In ICASSP (oral), 2018.
- Disentangled Representations of Style and Content for Visual Art with Generative Adversarial Networks In NIPS Workshop on Machine Learning for Creativity and Design, 2017.
- Dance Dance Convolution In ICML, 2017.
- Extended Convolution Techniques for Cross-Synthesis In ICMC, 2016.
- Applications of Genetic Programming to Digital Audio Synthesis Undergraduate honors thesis TR-2156, 2013.
- (Summer 2018) Internship at Google Magenta (Music generation w/ Ian Simon and Sander Dieleman)
- (Summer 2017) Internship at Google (Speech recognition w/ Bo Li and Rohit Prabhavalkar)
- (Summer 2016) Internship at Google Search
- (Summer 2015) Internship at Google Play Music (MIR w/ Nicolas Boulanger-Lewandowski)
- (2011-2014) Mentor for UT Freshman Research Initiative w/ Joel Lehman and Risto Miikkulainen
- (Summer 2014) Internship at Famigo
- (Summer 2013) Internship at Docbook MD
- (Summer 2012) Internship at Qualcomm
- (Summer 2011) Internship at UT Applied Research Laboratories
- UploadVR Beat Sage Update Adds 90 Degree Levels, Walls And Single Saber Mode
- UploadVR Get Rhythm: How Beat Sage Uses AI To Create Beat Saber Maps
- Road to VR This 'Beat Saber' Project Uses AI to Generate Custom Beat Maps for Any Song
- UploadVR New AI Tool Turns Any Song Into A Custom Beat Saber Map, And It Really Works
- Stereogum Watch The Flaming Lips Play A Bowl Of Fruit At Google I/O
- 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
- (2020) Released Beat Sage, a web service for automatically creating Beat Saber levels (link)
- (2020) Download files from Google Drive on the command line (link, code)
- (2019) PhD dissertation (pdf)
- (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 2020/05/18