Kemal Sonmez

Research Interests

I draw tools from statistical signal processing, systems theory, information theory, machine learning, pattern recognition, and neural computation in working on problems in:

Computational Biology: I am interested in discovery and implementation of algorithms that facilitate the understanding of biological processes. Particular applications have included pathway modeling, sequence-to-function analysis of genes and proteins, ontology/schema development for biological databases (, and determination of sleep/arousal states in rodents from electrophysiological recordings.

Statistical Signal Processing and Automatic Speech/Speaker Recognition: My work has concentrated on automatic speech and speaker recognition, especially robust speech recognition, modeling of prosody, and multiresolution speech representations. Earlier work has included information theoretic bases for estimation, and stochastic processes.