Georg M Goerg
From Santa Fe Institute Events Wiki
My path to SFI
I am a PhD candidate (starting 4th year) in [http://www.stat.cmu.edu/ Statistics at Carnegie Mellon]. I received my masters in mathematics (applied / econometrics) from the Vienna University of Technology, Austria and before coming to the US, I spent a year in Chile teaching statistics (mainly time series) at PUC.
In my thesis I work on local statistical complexity (LSC) - a measure of interestingness for spatio-temporal fields. We develop the statistical methods and algorithms to i) forecast a spatio-temporal system, and ii) discover patterns automatically solely from the data. We do this using modern non-parametric statistical / machine learning techniques with good properties for any kind of (complex) spatio-temporal system.
One reason why I work on spatio-temporal systems is that I have always been drawn to time series and methods that try to solve real-world problems. These include time series clustering, forecasting, blind source separation techniques for forecastable time series, time-varying parameter models. Another side-project are skewed and heavy-tailed distributions, in particular how we can transform random variables to introduce skewness and heavy tails. And as a statistician what's even more relevant to me is how can I reverse this transformation so I can take data and remove skewness, remove power laws, remove heavy tails (see Lambert W Random Variables).
For more details you can visit my website.
In my spare time I like to play soccer, volleyball, salsa dancing, traveling, ...