Andrea Zignoli

Power and pace profiling is extremely important in endurance training. The up-to-date estimations of the sustainable racing power or running and swimming pace can help coaches and athletes in monitoring training adaptations and performance potentials. There are different mathematical models that we can select to interpret the data we collect on the field. However, the selection of the right mathematical model for the real-world application often requires experience and computational effort. During this presentation, we will have the chance to create some examples with real world data, and to discuss why physiological profiling from field data is such an interesting and challenging research avenue.

Andrea Zignoli is a self-employed engineer who is specialised in the design of mathematical models of sport physiology and performance. He is interested in the application of deep learning technologies to the process of cardiopulmonary exercise tests and running kinematics, as well as the application of first-principles physics to the study of the 3D cycling dynamics. He is currently working as data scientist at Supersapiens (continuous glucose monitoring in athletes) and Athletica (web platform for automatic training plan generation), where he uses modelling techniques to guide product development.