This project pursues the goal of helping people who have lost their voices through illness or injury. Specialized Silent Speech interfaces are created for two patient groups, namely laryngectomees (who have lost their voice box, but still can perform articulatory movements) and persons with neurodegenerative diseases (who may not even be able to move their mouth). In the first case, we rely on the technique of captuing electromyographic activity (i.e. traces of muscle activity) from the user's face: while proof-of-concepts of this method have already been presented, this project will perform one of the first large-scale user studies, tackling many roadblocks which so far have prevented the creation of practically useful voice prostheses, ideally replicating the person's own voice. The second user group will be able to recreate speech by means of cerebral recordings (electrocorticography, ECoG).
This is a collaborative project with Prof. Tanja Schultz at the Cognitive Systems Lab at Bremen University, Germany. It is funded by the Swiss National Science Foundation and by the German Research Foundation.
I am also a consulting partner in the RessINT project, which receives national funding by the Agencia Estatal de Investigación (Spain) and is a companion project to MyVoice.
Application of Artificial Intelligence in the chemical and pharmaceutical industry is a highly current topic, in the light of recent innovation in machine learning, and the fast development of the field of chemistry. Therefore, there is a strong need to train a new generation of scientists who have competence in both machine learning and chemistry. This project, funded by the European Union (Marie Skłodowska-Curie European Industrial Doctorate, grant agreement No 956832) will provide a remedy: Sixteen excellent PhD candidates will be recruited by more than 20 partners, working on challenging topics selected to cover the key innovative directions in machine learning in chemistry. They will be supervised by academics who have excellent complementary expertise and contributed some of the fundamental AI algorithms which are used billions of times per day in the world, and by industry reearchers in leading EU Pharma companies. Beyond the scientific work of the individual fellows, the AIDD network will offer comprehensive, structured training through a well-elaborated Curriculum.
The PI of this project is Jür;rgen Schmidhuber. For further information refer to the Project Homepage.
Although IAD (Inherited Arrhythmogenic Diseases of the heart) are rare, they account for 50% of deaths related to cardiac diseases. In this project, we will develop the first personalised digital cardiac monitoring and alert system which focuses on IADs, based on breakthrough machine learning and signal processing algorithms, compatible with existing devices and connectable with local emergency services. SUPSI research is executed within the newly founded MeDiTech institute, project partners include highly innovative companies in Italy and Switzerland, as well as the EOC CadioCentro and the TicinoCoure foundation.