Research Member of Common Room
Based at Oxford Mathematics, Vinayak’s work is funded under the Oxford-Emirates Data Science Initiative and is headed by Prof. Peter Grindrod. Supervised by Prof. Jared Tanner, within the Data Science Research Group, Vinayak and his colleagues are working to advance our understanding about deep learning approaches.
“Although many recent studies have been proposed to explain and interpret deep networks, currently there is no unified coherent framework for understanding their insights. Our work here aims to mathematically study the reasons why deep architectures are working well, what they are learning and are they really addressing the problem they are built for. The aim is to develop a theoretical understanding of deep architectures, which in general processes the data with a cascade of linear filters, non-linearities, and contraction mapping via existing well understood mathematical tools.”
Before coming to Oxford, Vinayak completed his PhD at the Indian Institute of Technology, Mandi, India. He then went on to work as a postdoctoral researcher at Idiap Research Institute, Switzerland. His research interests include sparsity aware signal processing, machine learning, and speech/audio processing.