معرفی
Monty A. Escabi is an Associate Professor at the University of Connecticut. His research focuses on understanding the neural mechanisms underlying auditory perception and sound recognition, combining large-scale neural recordings with computational modeling and machine learning. He explores how the brain processes sounds in complex environments, aiming to develop advanced sound recognition technologies and treatments for hearing loss.
Education:
- 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
Research Interests: Dr. Escabi investigates the computational principles of natural hearing, focusing on spectrotemporal processing in auditory pathways. His work bridges signal processing and neuroscience to uncover how neural circuits encode sound features like temporal periodicity and acoustic envelopes. The Escabi Lab also develops neurotechnologies for high-resolution auditory cortex recordings.
Grants & Collaborations:
- National Science Foundation ($890,842): Cortical Specializations for Behavioral Discrimination of Temporal Shape and Rhythm of Sound (2014–2018)
- National Institutes of Health ($1,448,437): CRCNS: Role of Statistical Regularities in Neural Sound Coding (2015–2020)
Laboratory: The Escabi Lab (http://escabilab.uconn.edu) specializes in auditory neuroscience, employing multi-disciplinary approaches to study neural coding and its translational applications in hearing technology.
