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.

The complexity we are involved in, nowadays, is the result of the very fast changing of the world scenario from the point of view of social life, economy, shortage of resources, etc. Internet and social networks, a kind of virtual cyber-skin embracing the planet, have tightly interconnected people, infrastructures and economic systems. All these changes have been fostered by technology innovation and we can only expect, due to the pace of technology innovation, that more changes are to come.

Accurate identification of people’s pose in video is of great importance. Its applications include gesture-based controls such as Kinect and motion capture systems without markers. New York University researchers recently developed a deep learning architecture using both color and motion features for human pose estimation.

The Design and Implementation of Signal Processing Systems Technical Committee has the mission to promote and support activities of the IEEE Signal Processing Society in the areas of: i) design, development and implementation of signal processing systems; ii) design of algorithms with implementation in mind and iii) design of software tools and methodologies to support the design of signal processing systems.

The Bio Imaging and Signal Processing (BIPS) Technical Committee updates this month on awards, past and future competitions and more