Machine learning for Signal Processing

Dr. Bala RaviKumar
Professor CS and ES Departments, SSU

Cerent Engineering Science Complex, Salazar Hall 2009A
4:00 PM

Abstract – Machine learning is increasingly popular for solving a wide-range of problems. Instead of explicitly programming a computer to solve a problem, machine learning allows a computer to create a model based on sample solutions (called training set) and use the model to solve problems. Machine learning is routinely used to solve problems such as voice recognition, image classification, translation from one language to another etc. In this talk, we will survey the role of machine learning in the area of human-brain interface using the EEG and related signals.

Dr. Ravikumar received his Ph.D. at the University of Minnesota and has taught at the University of Minnesota, University of Rhode Island, and San Francisco State University. He has been with Sonoma State University since 2001. Ravi’s areas of interest include Algorithm Design, Theory of Computation, Pen-based computing, Data Mining, and Bioinformatics. He has supervised more than 25 Master's theses and 3 Ph.D. theses. He has served on the program committees of several international conferences, and most recently Ravi organized a conference on the Applications of Automata Theory in San Francisco in Summer 2008. He is currently co-editing a special issue of the International Journal of the Foundations of Computer Science.