Kamal Sen is an associate professor at the Hearing Research Center in the department of biomedical engineering at Boston University. His laboratory uses an integrative approach to investigate the neural coding of natural sounds in the auditory system, with a focus on auditory cortex. Electrophysiological techniques are used to record neural responses from hierarchical stages of auditory processing. Theoretical methods from areas such as statistical signal processing, systems theory, probability theory, information theory and pattern recognition are applied to characterize how neurons in the brain encode natural sounds. Computational models are constructed to understand the processing of natural sounds both at the single neuron and the network level, to model neural selectivity and discrimination, and to explore the role of learning in shaping the neural code. A major focus of the laboratory over the last decade has been to investigate cortical substrates for solving the Cocktail Party Problem.