SPS Feed

Bing Hu, (University of California, Riverside) “Mining Time Series Data: Moving from Toy Problems to Realistic Deployments” (2013) Advisor: Eamonn Keogh

A team led by Stanford electrical engineers has compressed a completely sequenced human genome to just 2.5 megabytes – small enough to attach to an email. The engineers used what is known as reference-based compression, relying on a human genome sequence that is already known and available. Their compression has improved on the previous record by 37 percent. The genome the team compressed was that of James Watson, who co-discovered the structure of DNA more than 60 years ago

Precision medicine is a new model of health care which gains insights from an individual's history and biology patterns, to create more precise diagnosis and treatment, at a lower cost. Precision medicine is a big data problem. Despite the completion of Human Genome Project more than ten years ago and the development in the field as a whole, precision medicine is still not a routine practice of medicine due to the lack of appropriate technical work and software platforms.

The Machine Learning for Signal Processing Technical Committee (MLSP TC) is involved with activities that support the use of Machine Learning techniques for Signal Processing problems. The scope of this TC is fairly wide, ranging from traditional machine learning and pattern recognition, to approaches that combine material from both disciplines. Under the scope of the MLSP TC we find areas such as source separation, graphical and kernel methods for time-series, Bayesian non-parametrics, and matrix and tensor factorizations among many more.

In this series, we introduce topics outside of the signal processing world from which we believe signal processing researchers and practitioners can benefit. This month, we report on a special issue on "Theoretical Foundations of Evolutionary Computation" published  by the IEEE Transactions on Evolutionary Computation.

The IEEE Signal Processing Society (SPS) announced the 2015 Class of Distinguished Lecturers. Five colleagues were honored and they are: Hynek Hermansky (Johns Hopkins University); Visa Koivunen (Aalto University); Hamid Krim (North Carolina State University); Jean-Christophe Olivo-Marin (Institut Pasteur); and Min Wu (University of Maryland).

The IEEE Internet of Things Initiative (IoT) announced it has launched its new IEEE IoT eNewsletter, a bi-monthly online publication highlighting important global IoT-related technology developments, innovations, and trends from the world's top-subject matter experts, researchers, and industry practitioners.

The IEEE Signal Processing Society Malaysia Chapter has been selected as the fourth recipient of the 2014 Chapter of the Year Award!

INTERSPEECH is the world’s largest and most comprehensive conference on the science and technology of spoken language processing. INTERSPEECH conferences emphasize interdisciplinary approaches addressing all aspects of speech science and technology, ranging from basic theories to applications.