The Image, Video, and Multidimensional Signal Processing Technical Committee (IVMSP TC) promotes and guides the advancement of the field of image, video, and multidimensional signal processing. It provides leadership for the technical programs for ICIP and for the IVMSP-related areas at ICASSP; recruits and volunteers reviewers for ICIP and for the IVMSP-related areas at ICASSP; assists in proposing and organizing ICIP; organizes and operates IVMSP workshops and sessions at ICIP and ICASSP; and participates in a range of other SPS activities.

The Signal Processing Theory and Methods (SPTM) TC reports on the 2015 Signal Processing/Signal Processing Education Workshop and new TC members

This Funding Opportunity Announcement (FOA) seeks applications that propose research studies that extend experimental protocols beyond the range of acoustic psychophysical research studies widely performed today. This will require design of algorithms and research studies that validate the potential benefits from these novel approaches to acoustic signal processing.

The special issue of the Proceedings of the IEEE in July is the second issue focusing on reconfigurable systems. In the first special issue (vol. 103, no. 3, 2015) introduced by eNewsletter in June, the foundational concepts are addressed. In this special issue, the editors focus on the basic concepts discussed in the first issue by considering more advanced applications, the extension of reconfigurability to other phenomenologies/domains, and the impacts of selected emerging technologies.

The Design and Implementation of Signal Processing Systems Technical Committee (DISPS TC) 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.

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.

The latest IEEE Biometrics Council (BMC) newsletter reports a welcome message from Venu Govindaraju, the new president of the IEEE BMC, latest datasets for fingerprint algorithm evaluation and a large biometrics-based human identification initiative in India.