Title

Maysam Nezafati

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Title/Position
Senior Lecturer
Contact

Contact

U.A. Whitaker, Office 1238Georgia Tech
404.385.4450
Education

Education

  • Ph.D. in Electrical Engineering , 2014 - University of South Florida
  • M.Sc. in Electrical Engineering , 2013 - University of South Florida
  • M.Sc. in Materials Science and Engineering, 2011 - The Royal Institute of Technology (KTH)
  • B.Sc. in Materials Science and Engineering, 2008 - The University of Tehran
Research Interests

Research Interests

My research focuses on brain network complexity, cognitive engagement, and motivation using multimodal neuroimaging techniques including fMRI, EEG, and physiological signals. Through entropy-based analysis and machine learning, my lab investigates how neural dynamics change across task conditions, cognitive load, and individual differences. A central goal of my work is to bridge laboratory neuroscience with authentic educational environments—developing AI-enabled models that detect engagement, predict learning outcomes, and inform equity-minded instructional design. 
In parallel, I lead research initiatives in engineering education, examining mentorship structures, entrepreneurial mindset development, and scalable undergraduate research ecosystems supported by NSF and the Kern Family Foundation. Together, these efforts advance a neurobiologically grounded, data-informed approach to improving learning experiences in engineering.

Teaching Interests

Teaching Interests

As a faculty in Biomedical Engineering, I teach core courses in conservation principles, biostatistics, and problems in biomedical engineering. I design structured, interactive learning environments that emphasize conceptual mastery, quantitative reasoning, and real-world application. My teaching philosophy centers on clarity, high expectations with high support, and the intentional integration of research and practice. I am particularly committed to mentoring undergraduate researchers and building inclusive, cohort-based research programs that expand access to meaningful scholarly experiences.
Publications

Publications

Abbas, A., Belloy, M., Kashyap, A., Billings, J., Nezafati, M., Schumacher, E. H., & Keilholz, S. (2019). Quasi-periodic patterns contribute to functional connectivity in the brain. Neuroimage, 191, 193-204.
Salarian, M., Turaga, R. C., Xue, S., Nezafati, M., Hekmatyar, K., Qiao, J., ... & Yang, J. J. (2019). Early detection and staging of chronic liver diseases with a protein MRI contrast agent. Nature communications, 10(1), 4777.
Nezafati, M., Temmar, H., & Keilholz, S. D. (2020). Functional MRI signal complexity analysis using sample entropy. Frontiers in neuroscience, 14, 700.
Charkhkar, H., Frewin, C., Nezafati, M., Knaack, G. L., Peixoto, N., Saddow, S. E., & Pancrazio, J. J. (2014). Use of cortical neuronal networks for in vitro material biocompatibility testing. Biosensors and Bioelectronics, 53, 316-323.
Keilholz, S. D., Pan, W. J., Billings, J., Nezafati, M., & Shakil, S. (2017). Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies. Neuroimage, 154, 267-281.

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