My name is Gaia and I have joined the CMS collaboration for three months as Summer Student at CERN. I completed my Bachelor in Physics in 2017 at the University of Padua and I am now attending a Master in Physics at the same institution. I had a great opportunity to take part in research work related to the use of machine learning to develop new statistical tools for detecting signals in particle physics.
My interest for Machine Learning began when I was in my last year of Bachelor and I came to know about the upcoming of neural networks application in High Energy Physics. I dealt with deep neural networks training for signal vs background discrimination. For the first time I realized how much power there is beyond artificial intelligence and how much scientists still ignore about that. This gave me the motivation to look for other opportunities to put machine learning tools in practice and see how much more it can provide.
At CMS I took part in a project dealing with the construction of a model-independent signal hypothesis based on the training of a neural network with a customized loss function. The work was still in progress so I could observe from the first row how a research activity could be carried on. On one hand, I could feel excited when things were working well and when new suggestions brought good results. On the other hand, I faced dead ends and failures. I could learn from both situations, for instance, on how to convince a colleague to pursue a new approach or to take a step back and change direction. I realized that a strong motivation and patience are required to keep on trying and to finally get a solution. I have learnt that questions are essential: they are not only useful for who is asking to clear up any doubts but also for who is answering, to test whether a new idea is robust or not. This helped me to become self-critical and self-confident too.
Experiencing the life at CERN is not only about work, it is also a human ex-change. For the first time I could share my life with students from all over the world. I could satiate my curiosity about how young people like me carry on their lives in different cultural environments. It was kind of surprise then to realize how many things are universal and most of all curiosity, excitement, and happiness: they could be conveyed even without a common language and they led us to make connections which became deeper and deeper as the days passed by. I hope my future career will give me the chance to meet my new friends again, maybe as workmates.
Besides more advanced knowledge in neural networks training, I have brought back home a new insight into what really researching is. I would thank my supervisors and all the people I worked with for the inspiring discussions and for the challenges which led me to do my best and to make the most of this experience. Still now it is for me a motivation to carry on this way for my future.
The views expressed in CMS blogs are personal views of the author and do not necessarily represent official views of the CMS collaboration.