The IEEE Meetings, Conferences & Events (MCE) Conference Education Program is offering the following upcoming webinars:

The IEEE Signal Processing Society (SPS) is honored to announce the elevation of 22 of its members to the grade of IEEE Senior Member. These members have demonstrated outstanding professional performance, exhibited professional maturity through long-term experience, and established themselves as leaders in their respective IEEE-designated fields of interest. Senior Member is the only membership grade that is eligible to be nominated for IEEE Fellow.

Machine learning, a subfield of computer science, has been widely applied in many areas from science to engineering to many interdisciplinary fields. Nature Reviews Genetics recently published an article that summarized machine learning applications in genetics and genomics, authored by University of Washington researchers Maxwell W. Libbrecht and William Stafford Noble. The topics of interest included supervised versus unsupervised learning, generative versus discriminative modeling, incorporating prior knowledge, handling heterogeneous data, feature selection, imbalanced class sizes, handling missing data, and modelling dependence among examples.

As a result of recent advances in MEMS/NEMS and systems biology, as well as the emergence of synthetic bacteria and lab/process-on-a-chip techniques, it is now possible to design chemical “circuits”, custom organisms, micro/nanoscale swarms of devices, and a host of other new systems at small length scales, and across multiple scales (e.g., micro to macro)

The Board of Governors of the IEEE Signal Processing Society (SPS) elected two new officers who will start their terms on 1 January 2016: Ali H. Sayed (University of California) will serve as 2016-2017 SPS President-Elect and Walter Kellermann (University of Erlangen-Nuremberg) will serve as 2016-2018 SPS Vice President-Technical Directions.

How fast is online learning evolving? Are wind turbines a promising investment? And how long before a cheap hoverboard makes it to market? Attempting to answer such questions requires knowing something about the rate at which a technology is improving. Now engineers at MIT have devised a formula for estimating how fast a technology is advancing, based on information gleaned from relevant patents.