Katerina Kosta
Machine Learning Researcher, Jukedeck, London (UK)
Katerina Kosta is a machine learning researcher at Jukedeck, working as part of the composition team whose aim is to develop machine learning systems for music generation. She pursued my PhD from the Centre for Digital Music, Queen Mary University of London, conducting research on modelling dynamic variations in expressive music performance. Other research interests during her studies included machine learning for music synthesis and analysis of perceived emotion in music audio. She received degrees from National and Kapodistrian University of Athens (Mathematics) and Filippos Nakas Conservatory, Athens (Piano), and a Sound and Music Computing Masters from the Music Technology Group, UPF, Barcelona.
Penny Lewis
Professor, Cardiff University, Cardiff (UK)
Penny Lewis is a neuroscientist specialising in sleep and cognition. Her work focuses largely on 'sleep engineering' - e.g. the science of manipulating sleep for cognitive and health benefits. Some of this work involves boosting or dampening the neural oscillations that occur in various sleep stages in order to increase their beneficial impacts. Another portion of this work focuses on the question of how memories are processed during sleep and how we can manipulate this by triggering the replay of specific memories or combinations of memories during specific stages of sleep. Recently, she has become interested in how such manipulations of memory consolidation impact on creativity, e.g. the restructuring or recombining of memories that underpins innovative thinking. As the repeated replaying of of multiple types of memory in multiple sleep stages across multiple nights is a complex problem, Penny is also interested in constructing computational models of this process in an attempt to gain a better grasp on it. Finally, Penny has a new project relating to 'humanlike' computing, and is interested in instilling sleep like off-line processing in Artificial Intelligence systems in order to see if it allows them to build a richer knowledge structure.
