Microsoft Research PhD Summer School 2016

I was lucky enough (thanks to Dr. Matteo Venanzi) to be invited to Microsoft’s summer school that takes place in Cambridge, UK, every year (4-8 July 2016). This is a one week school that aims to familiarise PhD students with the work at Microsoft. Moreover, students get the opportunity to present their work to other students, communication experts and Microsoft researchers. The benefit of this is twofold. First, students get feedback on their work and their presentation skills and style. Also, it is an opportunity to meet new people and measure the impact of your work in terms of the interest your poster attracts. At the same time, it is an opportunity to evaluate whether your work has any relevance to anything that Microsoft’s is currently working on. The school focuses on early PhD students but late students, like me, attended as well.

In terms of the everyday schedule, as I already mentioned, we had some coaching on how to communicate our research but we also had some more technical lectures as well. For example, I particularly liked Prof. Bishop’s presentation (“The Road to General Artificial Intelligence”). He focused on the advancements of AI in the recent years and that the potential is still greater.

Overall, I believe this yearly summer school is a great initiative from Microsoft Research and I am glad I was a part of it.


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Gaussian Process Summer School

Last September I had the opportunity to attend Gaussian Process Summer School, in Sheffield, UK. It is a twice a year event that holds for 3-4 days. First of all, I have to say that it was an awesome experience even if i had no much time to explore the city. Besides, it was heavy raining most of my time there. Well, we had an excursion to a local brewery.

Anyway, the event was structured like full day lectures, everyday, given by experts in the field. And by saying experts I mean  guys like Rasmussen, who has written the famous book on Gaussian Processes (GPs) cited on any paper that includes these two words nowadays, and of course Neil Lawrence who has a whole lab in Sheffield working on Gaussian Processes and organizes this School.

What I enjoyed the most though were the lab sessions scheduled between lectures. It was the perfect time to get our hands dirty. It was a chance to use GPy, a python library that includes almost everything about GPs, developed in Sheffield. I have to admit that GPy seems a lot more powerful tool to have than GPML which I currently (it is a GP library for Matlab). Anyway, the exercises given were perfectly suited to play around with the features of GPy as well as discover the potential of GPy and Gaussian Processes in general. In fact, the exercises were given in ipython notebooks. Ipython notebook is an interactive computational environment, in which you can combine code execution, rich text and mathematics. Specifically, we were given snippets of code that had some crucial parts missing, which we were supposed to fill in.

Another memory from the GP school was that of Joaquin Quiñonero Candela who gave lectures at the summer school as well as the university of Sheffield. Joaquin was previously a researcher at Microsoft and he is now director of research in Applied Machine Learning at Facebook,  where apparently make use of advanced machine learning techniques and push the field to its limits. Importantly Joaquin co-authored papers with Rasmussen  on Gaussian Processes and he seemed to me a brilliant guy.

That is pretty much my experience from this school. In another post, I will introduce GPs and explain as intuitively as i can their usefulness and applicability.