At BioBeats, we're working on projects that help people be well, fight stress, and be more productive. In most of these projects, deep learning approaches are taken to train models that can classify, predict and illuminate behaviour from the person's body and actions. Most of our classifiers learn from smartphone sensors, but increasingly our algorithms ingest from wearable sensors such as the Microsoft Band, Apple Watch, and upcoming projects from Google and Samsung. Our approach to building machine-learning-driven applications learns from evidence-based psychosocial intervention practices in mental health, but embodies continuous cardiovascular, skin, and movement-based sensor data in order to arrive at profound but granular insight for the individual, and their care or employer circle.
Researcher and entrepreneur, Davide leads BioBeats’ engineering team as CTO. He is a specialist in the intersection between Artificial Intelligence and music, previously ran a distributed software consultancy company in Italy for ten years. His PhD in Computer Science focuses on models that discover latent variables in performance profiles.