Marelie Davel is a Research Professor in the Faculty of Engineering of North-West University (NWU), and the Director of the Multilingual Speech Technologies (MuST) research group. Building on a long-standing interest in the theory and application of machine learning, her current research focuses on the generalisation ability of deep neural networks. Marelie obtained her undergraduate degrees (Computer Science & Mathematics) from Stellenbosch University, receiving the Dean’s medal as best student in the US Faculty of Science at the end of her Honours degree. Prior to joining NWU, Marelie was a principal researcher and research group leader at the South African CSIR, involved in technology-oriented research and development. Her research group focussed on speech technology development in under-resourced environments; in 2005, she received her PhD from the University of Pretoria (UP), with a thesis on bootstrapping pronunciation models, at the time one of the core ‘missing’ components when developing speech recognition for South African languages. In 2011, Marelie joined NWU, becoming the Director of MuST in 2014. MuST is a focussed research environment with an emphasis on postgraduate training and delivering on externally-focussed projects. Recent projects include the development of an automatic speech transcription platform for the South African government, development of a new multilingual text-to-speech corpus in collaboration with Internet giant Google, and being part of the winning consortium of the BABEL project: a 5-year internationally collaborative challenge aimed at solving the spoken term detection task for under-resourced languages. Over the past few years, Marelie has supervised 23 post-graduate students, all producing research related to the theory and applications of machine learning. She frequently participates in various scientific committees both nationally and internationally (AAAI, IJCAI, Interspeech, SLT, MediaEval, ICASSP, SLTU), is the NWU group representative at the national Centre for Artificial Intelligence Research (CAIR), and an NRF-rated researcher. Since 2003, she has published 100 peer-reviewed papers related to machine learning; she has an h-index of 21, and an i10-index of 37.