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.

The signal processing chapter of the IEEE Singapore Section was founded by me in 1989 with over twenty petitioners. It was established first as a special interest group in 1988 and subsequently in 1989 it was upgraded to the chapter status.

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).