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Georg M Goerg: Difference between revisions

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from the Vienna University of Technology, Austria and before coming to  
from the Vienna University of Technology, Austria and before coming to  
the US, I spent a year in Chile teaching statistics (mainly time series)  
the US, I spent a year in Chile teaching statistics (mainly time series)  
at PUC.
at PUC. For more details you can visit [http://www.stat.cmu.edu/~gmg/ my website].


== Research Interests ==
== Research Interests ==
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transformation so I can take data and remove skewness, remove power  
transformation so I can take data and remove skewness, remove power  
laws, remove heavy tails.  
laws, remove heavy tails.  
For more details you can visit [http://www.stat.cmu.edu/~gmg/ my website].


In my spare time I like to play soccer, volleyball, salsa dancing, traveling, ...
In my spare time I like to play soccer, volleyball, salsa dancing, traveling, ...

Revision as of 16:47, 2 June 2012

My path to SFI

I am a PhD candidate (starting 4th year) in Statistics at Carnegie Mellon. I received my masters in mathematics (applied / econometrics / time series) 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. For more details you can visit my website.

Research Interests

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.

In my spare time I like to play soccer, volleyball, salsa dancing, traveling, ...