The 8th Congress of the USERN Organization took place during the past three days (November 8-10, 2023) at the RAU University in Yerevan, Armenia, and it was a complete success, which has left me overwhelmed by the amount of great interdisciplinary science, fantastic art in multiple forms, and the intensity and rate of positive feelings I received throughout the event. I offer below a short report of the event and my impressions, which may of course be biased by being the President of this fantastic network, but does feel a rather trustworthy report now that I read it again.

Since most of the building blocks of our own body are protons, the above title might disturb sensitive readers. On the other hand, describing a proton as a bag of garbage has several merits, as it is a fruitful analogy that may be carried forward when we wish to examine experiments that studied the structure of matter. I will explain what I mean in a moment below.

The occasional reader of this blog will excuse me if yet again I do not report here of this or that new result by the LHC collaboration, and instead discuss matters of lesser relevance. But to me, education is important. Even if I am not a University professor, but rather an employee of a research institute (and as such, not obliged to spend some of my time teaching), I do teach courses to university students. I do that because I believe I can give students a positive imprinting on the beauty of physics, on the exciting nature of research in fundamental science, and on how interesting all of that is. 

As I am waiting in Prague airport for my flight back home, after a few days spent discussing the options of the SWGO collaboration for the detectors we are going to build, I came across (through compulsive scrolling on twitter) a thread that caught my attention. It was about emails to academics on PhD openings. Since I found the discussion there a bit too forgiving on the academics, I wish to express my position here - possibly in a less toxic environment.

Last week I received in my mailbox a copy of the Princeton University Press book "Machine Learning for Physics and Astronomy" by Viviana Acquaviva. They sent me a copy because I had reviewed its contents for Princeton Press.


I am happy with the book. When I accepted to review it, I was a bit hesitant because I am not a computer scientist. I might pass as an expert in machine learning because after all I have been developing such tools for 20 years now (or maybe I should say over 30, as my first attempt was in 1992, with a bootstrap-powered classification method), but I feel I still lack knowledge in some of the theoretical underpinnings, and there are holes in my knowledge base. 

Having spent the past 12 months coding up an end-to-end model of an astrophysics experiment, with the sole aim of searching for an optimal solution for its design by use of stochastic gradient descent, I am the least qualified person to judge the aesthetic value of the results I am finally getting from it. 
Therefore it makes sense to ask you, dear reader, what you think of the eerily arcane geometries that the system is proposing. I do not think that to be a good judge you need to know the details of how the model is put together, but I will nevertheless make an attempt at briefing you on it, just in case it makes a difference in your judgment.