Well, I've been dealing with astronomy, astrophysics and cosmology for quite some time, both as an undergraduate and a grad student.
The aim of this page is to give a very, very brief overview of all that happened back then.
I studied astronomy at the University of Bologna, Italy and I graduated with a thesis on gravitational lensing and cosmology in October 2005. Most of my thesis work was done in Heidelberg, Germany. From the end of 2005 till May 2009 I've been a PhD student in Heidelberg (again!) under supervision of Prof. Matthias Bartelmann.
The main point of my PhD thesis was to come up with methods to analyse cosmological data in a so-called model-independent way.
What does this mean?
When you look at cosmological data (that is, astronomical data that contain information about the origin/evolution of the Universe as a whole – examples are: distances to type-Ia supernovae, weak gravitational lensing due to the large-scale distribution of matter in the Universe, fluctuations in the cosmic microwave background, etc.) you want to extract the information about the Universe and its properties that is encoded in the data. BUT (!) in order to analyse and interpret the data to extract this information, you need to make certain assumptions about some properties of the Universe (could be the spatial geometry of the Universe, the density of its unknown components such as dark matter and dark energy, the velocity at which the Universe is expanding, etc.). The pitfall here is that, while you handle the data, you need to make assumptions on some of the very same properties that you later want to constrain using those data.
Or do you really? Maybe you don't need to make as many assumptions as you think you do. You can go the "model-independent" way. Of course, you can hardly be fully model-independent, because any fitting procedure you will apply to your data means that you are technically choosing a model. So our approach was to adopt a non-physically motivated model, just a purely mathematical one, and use it to reconstruct one of the main functions that underlies all cosmological observations: the Expansion Rate – which basically recounts the expansion history of the Universe. After you've determined this function in a reasonably model-independent way, then you can go and compare it to your favourite (physically motivated) model and draw whatever conclusion you may like.
As a chronic skeptical, I clearly liked the idea underlying this approach a real lot. In fact, this type of study goes well beyond the conclusions that you can draw about cosmology and the Universe, and concerns more the statistical methods that can be applied to parameter estimation in many other disciplines. Goes without saying that I also liked that a lot!
If you're curious and want to read more about all the gory details, you can have a look at these two papers: the method is presented here: Paper_Method and its extended version, making use of a way cooler statistical tool (i.e. principal component analysis) is presented here: Paper_PCA.
At the moment, I am no longer working on any research topics and I'm only occasionally collaborating with some former colleagues to keep alive some of the projects I've started (e.g. see Paper_Data). However, I thought it might be neat to post here the results. Just in case someone's interested.
Also, more important, during my PhD I've given a number of talks, both on my research work and on other topics.
I have to admit I really enjoy giving talks on other topics, and I used to spend lots of time preparing the slides.
I like to think that time wasn't wasted, and they might turn useful for someone sooner or later...
Presentations (varia) Presentations (my work) Refereed Papers Theses