I am a research engineer currently working at Gracenote in Emeryville, CA. I completed my PhD at the University of Auckland in the Forensics and Biometrics (FaB) signal processing lab. There I studied speech enhancement and learned a lot about the statistical modelling of both speech and many other environmental acoustic signals from a frequentist and Bayesian perspective. My thesis is available here.

Since completing my doctorate, I have continued to pursue my life-long passion for audio and music technology as a developer and research engineer at a number of excellent companies including Tait Communications, Serato and Gracenote. At these companies I have continued to develop skill sets in the areas of digital / statistical signal processing and machine learning while putting a lot of effort into quality software development pactices. I believe building extensible and maintainable codebases is an indispensible skill in creating modern technologies that have a strong impact in the real world.

Predominantly in the fields of Music Information Retrieval and Audio Signal Processing, my work has included researching, designing, implementing and improving a number of algorithms such as:

  • Noise Reduction
  • Automatic Equalisation
  • Genre Classification
  • Beat Tracking / Tempo Estimation
  • Song Structure Analysis
  • Time Stretching
  • Echo Cancellation
  • Active Noise Reduction
  • Audio Fingerprinting

Examples of such work exists in the Serato products Pyro and Sample. For a more detailed description of my past work and skill sets, view my Resume.

In my spare time I continue to develop software, and work on personal projects and curiosities. I love to go hiking, snowboarding, and play guitar or play around with Ableton Live.