Ted Meeds
I am currently a Postdoctoral Fellow at the University of Toronto, working with Brendan Frey analyzing yeast gene interactions. I just completed a PhD in the Machine Learning Group at the University of Toronto. My advisor was Sam Roweis.
My research focused on the application nonparametric Bayesian priors to novel machine learning models.
I am seeking employment as a Quantitative Researcher at hedge funds, prop trading firms, and investment banks. I am interested in applying Machine Learning techniques to financial time-series modeling and automated/systematic trading strategies.
Publications
Edward Meeds,
Nonparametric Bayesian Methods for Extracting Structure from Data,
Learning Stick-figure Models using Nonparametric Bayesian Priors over Trees,
Edward Meeds and Sam Roweis,
Nonparametric Bayesian Biclustering,
Modeling Dyadic Data with Binary Latent Factors,
An Alternative Infinite Mixture of Gaussian Process Experts,
Edward Meeds,
Novelty Detection Model Selection Using Volume Selection,
email: ewm[at]cs[dot]toronto[dot]edu
