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 586: Vector Space Methods with Applications
- 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
- Pratt Senior Creates Model to Predict How Self-Driving Cars Might Affect Traffic (Mar 3, 2017 | Pratt School of Engineering)
Representative Publications
- 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].
- Reeves, G; Pfister, HD, The Replica-Symmetric Prediction for Random Linear Estimation With Gaussian Matrices Is Exact, Ieee Transactions on Information Theory, vol 65 no. 4 (2019), pp. 2252-2283 [10.1109/TIT.2019.2891664] [abs].
- Bertran, M; Martinez, N; Papadaki, A; Qiu, Q; Rodrigues, M; Reeves, G; Sapiro, G, Adversarially learned representations for information obfuscation and inference, 36th International Conference on Machine Learning, Icml 2019, vol 2019-June (2019), pp. 960-974 [abs].