I once was an active chessplayer, but work duties have long taken tournaments off my plate - I simply do not have the time to sit through long hours of chess battles. So I play blitz online on chess.com (my handle is "tommasodorigo", in case you wondered).
I recently held an accelerated course in "Statistical data analysis for fundamental science" for the Instats site. Within only 15 hours of online lectures (albeit these are full 1-hour blocks, unlike the leaky academic-style hours that last 75% of that) I had to cover not just parameter estimation, hypothesis testing, modeling, and goodness of fit, plus several ancillary concepts of high relevance such as ancillarity (yep), conditioning, the likelihood principle, coverage, and frequentist versus bayesian inference, but an introduction to machine learning! How did I do?
A calorimeter in physics is something that measures heat. However, there are mainly two categories of such objects: ones that measure macroscopic amounts of heat, and ones that measure the heat released by subatomic particles when they smash against matter. I am sure you guess which is the class of instruments I am going to discuss in this article.A further distinction among calorimeters for particle physics is the one concerning the kind of particles these devices aim to measure. Electromagnetic calorimeters target electrons and photons, and hadronic calorimeters target particles made of quarks and gluons. Here I will discuss only the latter, which are arguably more complex to design.Smashing protons
In the past two weeks I visited two schools in Veneto to engage students with the topic of Artificial Intelligence, which is something everybody seems to be happy to hear about these days: on the 10th of January I visited a school in Vicenza, and on the 17th a school in Venice. In both cases there were about 50-60 students, but there was a crucial difference: while the school in Venezia (the "Liceo Marco Foscarini", where I have been giving lectures in the past within the project called "Art and Science") was a classical liceum and the high-schoolers who came to listen to my presentation were between 16 and 18 years old, the one in Vicenza was a middle school, and its attending students were between 11 and 13 years old.
From tomorrow onwards (once or twice a week until February 5), I will be giving an online course on the topic of "Statistical Methods for Fundamental Science" for the INSTATS organization. This is a 5-day, 15-hour set of lectures that I put together to suit the needs of students and researchers who work in any scientific discipline, who wish to improve their understanding and practice of statistical methods for data analysis.
2023 is over and I am looking back at my achievements and failures, to take stock and try to learn something from the matter. This blog looks like a reasonably good place for such an exercise, so I am writing here an inventory of what happened to me in the past 12 months. Sorry if this sounds very boring!
Next month I will be giving three lectures to high-school students on using artificial intelligence for research in fundamental physics, and as usual I am not yet worried by the schedule enough to start thinking at the presentations. Except that in one case the school professor who organizes the event asked me for some preliminary task for the students "to get them in the mood" of the contents of the lecture.
A number of Master courses in the STEM area mandate students to find a research project abroad to which they participate for 3-6 months. Many of the students find projects that arise their interest through internet searches- at least this is the way I got to know a few of them: as I regularly put details of my research progress in this blog (among other places), I am evidently a visible target. I do not complain about this: many of the students who contact me end up contributing to the projects they get embedded in. In return, they usually get to add a few lines to their CV, and maybe authorship of one or two papers.
In recent times, artificial intelligence has become ubiquitous. Besides powering our cellphones, directing what advertisements we get when we browse internet or read our emails, and creating content in the media, AI-powered hardware is more and more widespread, including self-driving vehicles, home appliances, and a host of other systems for industrial use.
Did you recently finish a Master in a scientific discipline, and wish to do some research before deciding whether to embark in a Ph.D.? Do you fancy coming to Padova and work with me and a team of physicists, computer scientists, and astrophysicists on detector optimization? Do you like the idea of traveling to Kaiserslautern for significant periods during the internship, to work under guidance of Prof. Nicolas Gauger at RPTU? Or do you know somebody to which the above might apply? Then please read on.
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.
