Areas of Expertise/Research
- Machine Learning
- Signal Processing
- Brain-Computer Interfaces
Ph.D., Telecommunications, 2008 (Institut National de la Recherche Scientifique, Canada)
M. A. Sc., Electrical Engineering, 2005 (Carleton University, Canada)
08/2022 - Current: City College of New York - Associate Professor (Biomedical Engineering)
08/2015 - 08/2022: City College of New York - Assistant Professor (Biomedical Engineering)
06/2013 - 07/2015: Stanford University - Research Associate (Psychology)
09/2008 - 05/2013: City College of New York - Post-Doctoral Fellow (Biomedical Engineering)
My research develops novel techniques for (i) non-invasively stimulating the brain and (ii) decoding neural signals. We are testing the transcranial application of ultrasound and near-infrared lasers to restore or enhance physiological activity in the central nervous system. Our efforts in neural decoding adopt a machine learning approach to infer brain states from neuroimaging data collected in naturalistic settings. We make extensive use of biophysical modeling of the human head as well as multivariate statistical techniques to optimize interventions and increase the sensitivity of our decoding methods. The research is expected to translate to new treatments for psychiatric and neurological disorders.
Dmochowski, J. P. (2022). Learning latent causal relationships in multiple time series. arXiv preprint arXiv:2203.10679.
Nguyen, D., Berisha, D., Konofagou, E., & Dmochowski, J. P. (2022). Neuronal responses to focused ultrasound are gated by pre-stimulation brain rhythms. Brain Stimulation.
Dmochowski, G. M., Shereen, A. D., Berisha, D., & Dmochowski, J. P. (2020). Near-infrared light increases functional connectivity with a non-thermal mechanism. Cerebral Cortex Communications, 1(1), tgaa004.