Galen Reeves

Galen Reeves

Assistant Professor in the Department of Electrical and Computer Engineering

Appointments and Affiliations

  • Assistant Professor in the Department of Electrical and Computer Engineering
  • Assistant Professor of Statistical Science

Contact Information

  • Office Location: 140 Science Dr., 321 Gross Hall, Durham, NC 27708
  • Office Phone: (919) 668-4042
  • Email Address: galen.reeves@duke.edu
  • Websites:

Education

  • Ph.D. University of California at Berkeley, 2011

Research Interests

Information theory; high-dimensional statistical inference; statistical signal processing; compressed sensing; machine learning.

Courses Taught

  • ECE 280L9: Signals and Systems - Lab
  • ECE 280L: Introduction to Signals and Systems
  • ECE 392: Projects in Electrical and Computer Engineering
  • ECE 493: Projects in Electrical and Computer Engineering
  • ECE 494: Projects in Electrical and Computer Engineering
  • ECE 587: Information Theory
  • ECE 741: Compressed Sensing and Related Topics
  • STA 563: Information Theory
  • STA 741: Compressed Sensing and Related Topics

In the News

Representative Publications

  • Kipnis, A; Reeves, G; Eldar, YC; Goldsmith, AJ, Compressed sensing under optimal quantization, IEEE International Symposium on Information Theory - Proceedings (2017), pp. 2148-2152 [10.1109/ISIT.2017.8006909] [abs].
  • Reeves, G, Two-moment inequalities for Rényi entropy and mutual information, IEEE International Symposium on Information Theory - Proceedings (2017), pp. 664-668 [10.1109/ISIT.2017.8006611] [abs].
  • Reeves, G, Conditional central limit theorems for Gaussian projections, IEEE International Symposium on Information Theory - Proceedings (2017), pp. 3045-3049 [10.1109/ISIT.2017.8007089] [abs].
  • Mainsah, BO; Reeves, G; Collins, LM; Throckmorton, CS, Optimizing the stimulus presentation paradigm design for the P300-based brain-computer interface using performance prediction., Journal of Neural Engineering, vol 14 no. 4 (2017) [10.1088/1741-2552/aa7525] [abs].
  • Mainsah, BO; Collins, LM; Reeves, G; Throckmorton, CS, A performance-based approach to designing the stimulus presentation paradigm for the P300-based BCI by exploiting coding theory, IEEE International Conference on Acoustics Speech and Signal Processing (2017), pp. 3026-3030 [10.1109/ICASSP.2017.7952712] [abs].