November 2018

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2018

Volume 35 | Issue 6

The Advertisers Index contained in this issue is compiled as a service to our readers and advertisers: the publisher is not liable for errors or omissions although every effort is made to ensure its accuracy. Be sure to let our advertisers know you found them through IEEE Signal Processing Magazine.

The Bio-Imaging and Signal Processing Technical Committee (BISP-TC) of the IEEE Signal Processing Society (SPS) promotes activities in the broad technical areas of computerized image and signal processing with a clear focus on applications in biology and medicine.

As part of the IEEE Signal Processing Society (SPS), the Speech and Language Technical Committee (SLTC) promotes research and development activities for technologies that are used to process speech and natural language.

In the era of big data, analysts usually explore various statistical models or machine-learning methods for observed data to facilitate scientific discoveries or gain predictive power. Whatever data and fitting procedures are employed, a crucial step is to select the most appropriate model or method from a set of candidates. 

The title of this editorial is borrowed from a popular children’s lullaby from the 1800s, which reads “Twinkle, twinkle, little star, how I wonder what you are!” It reminds me of the vast expanse of unexplored space (and science) that lie before us. 

There have been three key revolutions in the way that research has become accessible: publishing, code, and data. The second and third revolutions are still taking place, particularly driven by the rise of machine-learning and artificial intelligence research in the last decade. When I started my research career in 1995, the World Wide Web was still in its infancy. 

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