Konstantinos Trochidis has a background in machine learning, statistical modeling and audio recognition. He worked as a Postdoctoral researcher in France at the University of Burgundy (2010-2011) in Canada (2011-2013) at McGill and McMaster Universities, in Singapore at the Singapore University of Technology and Design (2013-2015) and New York University in Abu Dhabi (2015-2018). During his research at NYUAD and MaSC he worked on the development of machine learning models for carnatic music generation and on the perceptual rhythm similarity of Arabic music. He also developed data visualisation methods and non-linear mappings of unstructured music data for recommendation of Arabic music.
He is currently working as a Lead AI & ML Engineer at Siemens Financial Services (SFS) to support the Digitalization and automation initiatives of SFS using Machine/Deep Learning and NLP.