The Analytics of Big Data

José M. F. Moura, Ph.D.

Philip L. and Marsha Dowd University Professor, Carnegie Mellon University

Traditionally, we have processed data as speech signals, audio, or more generically time series, as well as images, or videos; all these data are indexed by time ticks and pixels. The last few years have seen an explosion of data, Big Data, arising from a very diverse set of applications where signals and data are now indexed by social agents, genes, customers, or some other enumeration suggested by the application. This has given rise to new tools to process these data. We will discuss a number of them, from graph signal processing to deep learning, in the context of several applications, from IoT to urban datasets.

Work with Jonathan Mei, John Shi, Mark Cheung, Yang Li, Shanghang Zhang, João P Costeira.

Ack: NSF grant CCF-1513936

José M. F. Moura, www.ece.cmu.edu/~moura, is the Philip L. and Marsha Dowd University Professor at CMU, with interests in signal processing and data science. A detector in two of his patents with Alek Kavcic is found in over 60% of the disk drives of all computers sold worldwide in the last 15 years (4 billion and counting)–leading to a US $750 Million settlement between CMU and Marvell. He is the 2019 IEEE President and CEO. He was Editor in Chief for the Transactions on SP. Moura received the IEEE Signal Processing Society Technical Achievement Award and Society Award. He is Fellow of the IEEE, AAAS, and the US National Academy of Inventors, corresponding member of the Academy of Sciences of Portugal, and member of the US National Academy of Engineering. He received the Grã Cruz of the Ordem do Infante D. Henrique bestowed to him by the President of the Republic of Portugal.