Nima Mesgarani
Associate Professor Of Electrical Engineering
Nima Mesgarani’s research is focused on the exploration of human speech communication. He studies representational and computational characteristics of the human brain areas involved in naturalistic speech communication.
He integrates these attributes into novel mathematical models used in machine emulation of speech communication. Better models of the underlying neural mechanisms involved in speech processing can critically impact research in artificial intelligence, neurolinguistics, systems neuroscience, translational medicine, and brain-computer interfaces.
Neurophysiology of Speech Communication
The process by which acoustic signals received by a listener are transformed into linguistic and non-linguistic categories is mainly unknown. Using the latest advances in invasive and non-invasive human recording techniques, Mesgarani’s group aims to uncover fundamental characteristics of cortical speech processing that enable a listener to extract information from the speech signal.
Neuro-inspired Computational Models
Mesgarani’s research in this area focuses on advancing and refining artificial neural network models used to emulate the cognitive abilities of humans. Furthermore, it is crucial to understand better the representation and transformation performed by these models to identify their limitations and compare them accurately with their biological counterparts, thereby reducing the performance gap between biological and artificial computing.
Brain-Computer Interfaces
A better understanding of how speech communication occurs in healthy brains enables better therapeutic approaches to help those suffering from speech and language disorders or those who suffer from peripheral and central auditory pathway disorders. Mesgarani’s research includes better neural decoding algorithms and novel solutions for cognitively controlled hearable devices.
Nima Mesgarani is an associate professor of Electrical Engineering at Columbia University. He received his Ph.D. from the University of Maryland, where he worked on neuromorphic speech technologies and neurophysiology of the auditory cortex. He was a postdoctoral scholar at the Center for Language and Speech Processing at Johns Hopkins University and the University of California San Francisco neurosurgery department before joining Columbia in the fall of 2013.
Research Areas
- Speech neurophysiology
- Deep neural network models
- Brain computer interfaces
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Professional Experience
- Associate Professor, Department of Electrical Engineering and Zuckerman Mind Brain Behavior Institute (ZMBBI), Columbia University, 2020-
- Assistant Professor, Department of Electrical Engineering, Columbia University, 2013-2020
- Postdoctoral Scholar, Department of Neurological Surgery, University of California San Francisco. 2010-2013
- Postdoctoral Scholar, Center for Language and Speech Processing, Johns Hopkins University, 2008-2010
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Honors & Awards
- 2022 IEEE Signal Processing Society Best Paper Award
- 2022 Misha Mahowald Prize for Neuromorphic Engineering
- 2019 Top-10 Health Innovation of the Year award, Health Innovations magazine
- 2019 Top-10 breakthroughs of the year award, Institute of Physics
- 2018 & 2019 Grand prize winner at NYC Media Lab
- 2018 Young Investigator Award, Advances and Perspectives in Auditory Neuroscience, San
- 2018 Top 10 most significant and promising tech innovators of the year award, UNICEF
- 2016, National Science Foundation (NSF), Faculty Early Career Development Award
- 2015, Pew Charitable Trust, Pew Scholar in the Biomedical Sciences Award
- 2015, Research Initiatives in Science and Engineering Award (RISE)
- 2015, Kavli Institute for Brain Science Award
- 2005, George Harhalakis Outstanding Systems Engineering Graduate Student Award
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Education
- PhD, Electrical Engineering, University of Maryland College Park
- MS, Electrical Engineering, University of Maryland College Park
- BS, Electrical Engineering, Sharif University of Technology