👋 Hi, I’m Andrea, a self-employed engineer who creates mathematical models of sport physiology and performance.
I might be partly responsible for:
🫁 The spread of deep learning technologies in the process of cardiopulmonary exercise tests
🚴 The introduction of the concept of the adherence ellipse in road cycling
I’m equally interest in each phase of modelling: conceptualization and formalization, data collection and processing, model development and model deployment. I always value more the model that can teach us more in return. I love adding intelligence to the process. Ironically, more intelligence usually means less technology. And that’s the way it should be: sensors come and go, but learning is forever.
Why mathematical models?
Modelling lies at the heart of how we understand the world and its emerging properties. Mathematical modelling, in particular, is the process to describe a system with mathematical terms. The clear advantage of having our models written in a communicable language is that we can share our ideas with the world. If we are lucky enough, we share ideas that can be both innovative and helpful, and we get to participate in advancing the human knowledge.
Why sport physiology and performance?
I enrolled in an engineering course to study robotics, and I ended up by studying the most wonderfully made machine: the human body. Sport performance requires a combination of the best qualities of a human body, hence is human movement in its best form. Physiology is what makes movement possible, hence is human movement in its fundamental terms.