
Behtash Babadi
دانشیار · Statistical and Adaptive Signal Processing
University of Maryland, College Parkمعرفی
Behtash Babadi is an Associate Professor in the Department of Electrical & Computer Engineering and a faculty member at the Institute for Systems Research and the Brain and Behavior Institute at the University of Maryland, College Park. He also holds affiliate appointments in the Program in Neuroscience & Cognitive Science and the Applied Mathematics & Statistics program.
Education:
- Ph.D. in Engineering Sciences, Harvard University (2011)
- M.Sc. in Engineering Sciences, Harvard University (2008)
- B.Sc. in Electrical Engineering, Sharif University of Technology (2006)
Research Interests:
Dr. Babadi’s work focuses on statistical and adaptive signal processing frameworks for understanding neural systems. Key areas include:
- Neural signal processing and systems neuroscience
- Granger causality and functional connectivity analysis
- Dynamic modeling of neuronal assemblies
- Applications to auditory processing and cognitive recovery
Scientific Contributions:
His recent publications address cortical network dynamics, MEG source analysis, and robust causal inference. Notable methods include Network Localized Granger Causality (NLGC) for direct connectivity estimation and multitaper spectral analysis for neuronal spiking data.
Awards:
- NSF CAREER Award (2016)
- E. Robert Kent Teaching Award (2019)
- GSAS Merit Fellowship (Harvard, 2010)
Collaborations:
Dr. Babadi collaborates with institutions like MIT, Harvard, and Massachusetts General Hospital, and participates in interdisciplinary initiatives such as the Brain and Behavior Initiative (BBI) and NIH BRAIN grants.





