Luc Evers’ research combines neuroscience and data science to produce unobtrusive wearable sensors for monitoring Parkinson's disease (PD) in daily life. He studied medicine at the Radboud University, taking part in the Honors Academy of Medical Sciences. During his PhD (at the Donders Institute for Brain, Cognition and Behaviour and the Radboud Institute for Computing and Information Sciences), he specialized in machine learning and signal processing, with projects varying from the development of algorithms to using sensor-based outcomes to inform people with PD and their healthcare providers. His key contributions include the creation of a new reference dataset capturing unscripted activities at home, and the development of novel methods to quantify free-living gait and tremor. As part of his current postdoctoral research, Evers focuses on developing open-source software to process raw sensor data into digital progression biomarkers, capturing both motor and non-motor symptoms in early stage PD