Pietro Lio’ has a PhD in Genetics and a PhD in Complex Systems and is a scientist who works on artificial intelligence and medicine at the University of Cambridge. Email: email@example.com.
My research interest focuses on using bioinformatics, computational biology models and machine learning (deep learning) to integrate various types of data (molecular and clinical, drugs, social, cognitive behaviour and lifestyle) across different spatial and temporal scales of biological complexity to address personalised and precision medicine. A particular concern is on the data security and the privacy against inference methods.
In the context of basic science, these approaches are effective in understanding the mechanisms and the dynamics of how biological elements build up properties such as sensing the environment, information carrying, being programmable and doing computation and communication. In the context of biomedical fields, by integrating different layers of evidences, predictive models will improve the accuracy of diagnosis of complex diseases in presence of other chronic and acute conditions, will identify effective markers for disease trajectory and suggest composition of treatments (drugs and lifestyle) before the manifestation of symptoms.