Galen Reeves

Associate Professor in the Department of Electrical and Computer Engineering

Appointments and Affiliations

• Associate 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:
  • website

Education

• Ph.D. University of California, 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 587: Information Theory
• ECE 741: Compressed Sensing and Related Topics
• ECE 899: Special Readings in Electrical Engineering
• STA 563: Information Theory
• STA 741: Compressed Sensing and Related Topics
• STA 993: Independent Study

In the News

• Modeling Traffic with Self-Driving Cars (Mar 2, 2017 | Pratt School of Engineering)

Representative Publications

• Mathews, H; Mayya, V; Volfovsky, A; Reeves, G, Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise, 2019 Ieee 8th International Workshop on Computational Advances in Multi Sensor Adaptive Processing, Camsap 2019 Proceedings (2019), pp. 699-703 [10.1109/CAMSAP45676.2019.9022612] [abs].
• Reeves, G; Xu, J; Zadik, I, All-or-Nothing Phenomena: From Single-Letter to High Dimensions, 2019 Ieee 8th International Workshop on Computational Advances in Multi Sensor Adaptive Processing, Camsap 2019 Proceedings (2019), pp. 654-658 [10.1109/CAMSAP45676.2019.9022473] [abs].
• Mayya, V; Reeves, G, Mutual Information in Community Detection with Covariate Information and Correlated Networks, 2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019 (2019), pp. 602-607 [10.1109/ALLERTON.2019.8919733] [abs].
• Reeves, G; Mayya, V; Volfovsky, A, The Geometry of Community Detection via the MMSE Matrix, Ieee International Symposium on Information Theory Proceedings, vol 2019-July (2019), pp. 400-404 [10.1109/ISIT.2019.8849594] [abs].
• Kipnis, A; Reeves, G, Gaussian Approximation of Quantization Error for Estimation from Compressed Data, Ieee International Symposium on Information Theory Proceedings, vol 2019-July (2019), pp. 2029-2033 [10.1109/ISIT.2019.8849826] [abs].