Monty A. Escabí
- B.S., Electrical Engineering, Florida International University, 1993
- M.S., Electrical Engineering: Signal Processing and Stochastic Modeling, Columbia University, 1995
- Ph. D., Bioengineering, University of California at Berkeley and San Francisco, 2000
I am broadly interested in understanding single neuron and network-level computations that underlie auditory perception and natural sound recognition capabilities, both for normal and impaired hearing. It is very easy for animals (including humans) to detect and discriminate vocalizations in the midst of high background noise and yet it is still not clear how this process is achieved within the central nervous system. This ability can be severely compromised in individuals with hearing loss. Artificial systems for voice recognition and hearing aids also fail miserably in the presence of competing environmental noise. Currently we are using a number of techniques, ranging from electrophysiology, psychoacoustics, computational modeling and machine learning in order to gain insight into this basic hearing process. This three-tiered approach allows us to identify biological principles that underlie hearing capabilities while simultaneously allowing us to develop a general theory that accounts for cognitive processes and signal processing computations underlying normal and impaired hearing.