The talk will first review the emerging field of graph signal processing, where the basic concepts will be discussed. Graph signal processing deals with development of mathematical tools for consistent analysis and processing of signals or data occurring over networks or graphs. The framework, by the way it is formulated, is directly applicable to a wide range of applications from sensor networks, biological, to traffic networks. Arun will also discuss his recent work on kernel regression and graph signal processing.
Dr. Arun Venkitaraman received his Bachelors degree in Electrical and Electronics Engineering from the National Institute of Technology Calicut (NITC) in 2010. Arun thereafter proceeded to obtain his Masters in Science (Engg.) from the Department of Electrical Engineering at the Indian Institute of Science Bangalore (IISc.), with specialisation in Signal Processing in 2013. Arun later worked as a research intern at the Philips Innovation Campus, Bangalore in the Healthcare research wing. Arun recently obtained his PhD from the School of Electrical Engineering and Computer Science, at KTH Royal Institute of Technology, Stockholm, Sweden. During his PhD, Arun was also a visiting researcher at EPFL, Switzerland. Arun’s research interests include graph signal processing, machine learning, artificial neural networks, sparsity and dimensionality reduction, harmonic analysis and modulation analysis.