New job starting next week :)

I am currently a research fellow and a Stats PhD candidate at NTNU under the supervision of Håvard Rue. I have spent a great four years in the INLA group. No words can express how much I am grateful to Håvard, who has been a good friend and an amazing supervisor (and a great chef I must say).

My PhD thesis will be a collection of six papers ranging from Bayesian computation to the design of sensible Bayesian models through an interesting framework to construct prior distributions. The thesis is almost done and I will at some point cover its main ideas on this blog. We are very happy with the work we have done in these four years. My PhD defense should happen around September this year.

As the saying goes, all good things must come to an end, and Friday is my last day at NTNU. However, I am very excited with my new job.

Starting on Monday (March 3rd), I will work as a Data Scientist at Yahoo! I will be located at the Trondheim (Norway)’s office, which is very fortunate for me and my wife, but will of course collaborate with the many Yahoo! Labs around the world. This was the exact kind of job I was looking for, huge amounts of data to apply my data analysis skills. I am sure I have a lot to contribute to as well as learn from Yahoo! I am looking forward to it.

My plan for this blog is to continue on the same path, posting about once a week on a subject that interests me, usually involving data analysis. My new job will probably affect my interests, and this will of course impact what I write on the blog. So, expect to see more stuff about Big Data and Text Analysis, although I will not restrict my interests on those subjects. Besides, it is always good to remind that this is my personal blog and there is no connection with any job I have at any moment, so opinions here are my own.

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INLA group

Update: As of March 2014 I am no longer a Research Fellow at NTNU, see here.

I am currently a PhD candidate at NTNU within the statistics group. And within the statistics group, we have a smaller group led by Håvard Rue that are sometimes informally called the INLA group. Now, what is INLA?

INLA stands for Integrated Nested Laplace Approximations and is an approach proposed by (Rue et al., 2009) to perform approximate fully Bayesian inference on the class of latent Gaussian models (LGMs). INLA makes use of deterministic nested Laplace approximations and, as an algorithm tailored to the class of LGMs, it provides a faster and more accurate alternative to simulation-based MCMC schemes.

The range of models that belong to the LGM family, and hence can be handled by INLA, are enormous and represent many of the most commonly used models by the applied community. Our group provide an R package called INLA that allow the user to specify complex models using the easy to use formula syntax available in R.

Please visit our page for more information about INLA and its R package. The website contains several worked out examples, papers and even the complete source code of the project. I also plan to write, among other things, about INLA on my blog posts from time to time.

References:

Rue, H. and Martino, S. and Chopin, N., 2009. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. Journal of the Royal Statistical Society: Series B(Statistical Methodology).