The convergent development of different technologies is bringing the understanding of the brain, both on healthy and pathological condition, further than ever before. The confluence of Wearables, Neurotechnologies, Augmented and Virtual Reality, Serious Gaming, Data Science, Machine Learning and Artificial Intelligence are a game changer in the way we study brain functionality, make use of it for interacting with the environment, and treat mental and neurological disease.
The talk will deal with the combination of Neurotechnologies, Machine Learning and Artificial Intelligence in different Digital Brain Health applications developed at Starlab Neuroscience. Digital markers of brain function will lead in the near future to improved diagnostic, drug discovery, risk analysis, and interactivity. We will show developed methodologies for: stratified performance evaluation of classifiers in operational conditions for Parkinsons’ risk assessment, differential diagnosis in ADHD based on Reservoir Computing, and new treatment outcome prediction in Coma patients. I will go over the technical challenges we faced to develop these applications, but also over some insights that influence the applicability of pure academic data science in the real world.
Dr. Aureli Soria-Frisch completed his education with a ‘Dr.-Ing.’ degree (equivalent PhD) from the Technical University Berlin in 2005. Between 1996 and 2005 he worked at the Department for Security Technologies of the Fraunhofer IPK (Berlin), where he participated in several funded research and industrial projects as research scientist and project leader. After working for 3 years at the Universitat Pompeu Fabra and part time in Starlab, he joined the company devoted to technology transfer of Data Science in 2008. He is currently the Director of the Neuroscience Business Unit of Starlab.
His research interest is focused on the fields of: data and multi-sensory fusion, computational intelligence for data analysis, and machine learning for brain data. He has authored 20 journal papers, 9 book chapters, and over 60 conference papers. He was Project Manager of the FP7 HIVE project, and holder of 2 MJFF grants for the discovery of Machine Learning based Parkinsons' biomarkers. He is coordinator of the H2020 FET Open project LUMINOUS, which studies human consciousness and different related technologies.
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