AI and wearable sensors to enable Digital Clinical Trials

Giorgio Quer's research focuses on artificial intelligence and probabilistic modeling applied to heterogeneous data signals, in order to extract key information and make predictions on future occurrences based on past data. He is involved in several digital medicine initiatives within the Digital Trial Center. In the DETECT study, he is developing algorithms to predict COVID-19 and other viral infections from wearable sensor data. He is responsible for the collaboration with several industrial partners, studying changes in heart rate and sleep data monitored by commercial wearable devices, and with the Halıcıoğlu Data Science Institute at UC San Diego. He is interested in the detection and modeling of atrial fibrillation from single-lead ECG signals. He received his Ph.D. degree in Information Engineering from the University of Padova, Italy, and he continued his studies as a Postdoctoral researcher with the Qualcomm Institute at UC San Diego. He is a Senior Member of the IEEE and a Distinguished Lecturer for the IEEE Communications society.