I am currently a PhD student at the University of California, San Diego studying computer music. I am jointly advised by Miller Puckette (music) and Julian McAuley (computer science). My main research focus is machine learning for audio signal processing and music information retrieval.
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.
- Semantically Decomposing the Latent Spaces of Generative Adversarial Networks arXiv:1705.07904, 2017.
- Dance Dance Convolution In Proceedings of the International Conference on Machine Learning, 2017.
- Extensions to Convolution for Generalized Cross-Synthesis Master's thesis, 2016
- Extended Convolution Techniques for Cross-Synthesis In Proceedings of the International Computer Music Conference, 2016
- Applications of genetic programming to digital audio synthesis Undergraduate honors thesis TR-2156, 2013
- (Summer 2017) Internship at Google (Speech Recognition w/ Bo Li)
- (Summer 2016) Internship at Google Search
- (Summer 2015) Internship at Google Play Music (MIR w/ Nicolas Boulanger-Lewandowski)
- (Summer 2014) Internship at Famigo
- (Summer 2013) Internship at Docbook MD
- (Summer 2012) Internship at Qualcomm
- (Summer 2011) Internship at UT Applied Research Laboratories
- (2011-2013) Mentor for UT Freshman Research Initiative w/ Joel Lehman and Risto Miikkulainen
I enjoy developing real-time audio applications. Using the Web Audio API, I built a waveshaper and a tree-based synthesizer. I also wrote a mobile-friendly music controller networked to a multi-user sound-synthesis server. Using JUCE, I built a VST plugin called melder (Windows binary) that performs real-time, multichannel convolution reverb. As a project for a graphics course, I wrote a 3D spectrogram (code). When I lived in Austin, I played in a band called Food Group. If you're insane, you might be looking for my Ph.D. qualifying examination.
Last updated 2017/06/11