About
Gianluca Rosso
I'm a statistician with a passion for sport.
I graduated from the University of Turin and I am an ordinary member of the SIS Società Italiana di Statistica of Rome. I was a Graduate Statistician (GradStat) of the Royal Statistical Society of London.
After some statistical research on the results of Formula 1, together with my colleague Luca Malfatti I founded QUANT4SPORT, a research and teaching network completely dedicated to the world of sport. Over the past few years, through the network, I have developed research on sports performance. The disciplines on which the analysis models have been developed are Formula 1, Formula E, football, tennis, basketball, skiing.
Here examples of AI analytics on YouTube.
In 2017 I created the first worldwide Repository of academic papers dedicated to sports. It is an archive accessible for free to anyone from the QUANT4SPORT site. Students, in particular, have the opportunity to deposit their analysis works in order to gain visibility. I am very attentive to the future developments of sport, especially in relation to technology. I have a look at e-sports, injury prevention, Para-athletics, youth and gender sports.
Since 2018 I have been teaching Sport Analytics at the Department of Economics and Statistics "Cognetti de Martiis" of the University of Turin as a contract professor, but I participate in courses and seminars when and where required.
In 2020 QUANT4SPORT won the Sport Innovation Awards as the best innovative teaching project.
I was also an artist, present in important private and public collections around the world. I am a big fan and collector of guitars, especially Fender of the past years.
A special note.
I follow organizations that deal with hearing loss and tinnitus, and all related psychological problems. In particular, pharmaceutical companies that are experimenting with treatments for the regeneration of hair cells. Through social networks, and in particular LinkedIn, you can follow these progress. I’m available to exchange information in this regard.
I'm a statistician with a passion for sport.
I graduated from the University of Turin and I am an ordinary member of the SIS Società Italiana di Statistica of Rome. I was a Graduate Statistician (GradStat) of the Royal Statistical Society of London.
After some statistical research on the results of Formula 1, together with my colleague Luca Malfatti I founded QUANT4SPORT, a research and teaching network completely dedicated to the world of sport. Over the past few years, through the network, I have developed research on sports performance. The disciplines on which the analysis models have been developed are Formula 1, Formula E, football, tennis, basketball, skiing.
Here examples of AI analytics on YouTube.
In 2017 I created the first worldwide Repository of academic papers dedicated to sports. It is an archive accessible for free to anyone from the QUANT4SPORT site. Students, in particular, have the opportunity to deposit their analysis works in order to gain visibility. I am very attentive to the future developments of sport, especially in relation to technology. I have a look at e-sports, injury prevention, Para-athletics, youth and gender sports.
Since 2018 I have been teaching Sport Analytics at the Department of Economics and Statistics "Cognetti de Martiis" of the University of Turin as a contract professor, but I participate in courses and seminars when and where required.
In 2020 QUANT4SPORT won the Sport Innovation Awards as the best innovative teaching project.
I was also an artist, present in important private and public collections around the world. I am a big fan and collector of guitars, especially Fender of the past years.
A special note.
I follow organizations that deal with hearing loss and tinnitus, and all related psychological problems. In particular, pharmaceutical companies that are experimenting with treatments for the regeneration of hair cells. Through social networks, and in particular LinkedIn, you can follow these progress. I’m available to exchange information in this regard.
