ProfileGraduated from world-famous Centre for Digital Music (C4DM), Queen Mary University of London (QMUL), Shengchen Li has focused on machine listening techniques on various types of signals including music, acoustic signal and biomedical signal. Being a pianist in young age, Shengchen has a special interest in computer music research including but not limited to automatic music generation, computational musicology and objective evaluation of piano performance.
His fellow students have named among the winner / top-ranked teams of IEEE AASP Data Challenge on Detection and Classification of Acoustic Scenes and Events (DCASE), which is a competitive and top-ranked data challenge in acoustic signal processing society, in the year of 2018-2021.
Shengchen is currently the leader of research group of machine learning and data analytics. He also has a fee studentship available for application at this stage. You are also more than welcome to visit Shengchen's personal webpage at https://shengchenli.github.io/ for details.