MARK A. DAVENPORT
Rice University, MS-366 Tel: (832) 244-9151
P.O. Box 1892 Email: md@rice.edu
Houston, TX 77251-1892 Web: http://www.ece.rice.edu/~md
RESEARCH INTERESTS
Signal processing and machine learning using low-dimensional signal models
Low-rate signal sensing and acquisition; compressed sensing
Kernel methods and support vector machines
EDUCATION
Currently pursuing a Ph.D. in Electrical Engineering at Rice University.
M.S. in Electrical Engineering from Rice University, May 2007.
Thesis: “Error control for support vector machines”
B.S.E.E in Electrical Engineering from Rice University, cum laude, May 2004.
B.A. in Managerial Studies from Rice University, cum laude, May 2004.
ACADEMIC POSITIONS
Research Assistant to Richard Baraniuk, Department of Electrical Engineering, Rice
University. 2005 to Present.
Teaching Fellow for Introduction to Signals and Systems (ELEC 301), Department of
Electrical Engineering, Rice University. Fall 2006, 2007. Regularly delivered lectures (in-
class), provided one-on-one assistance to students, assisted in writing assignments/tests,
and coordinated grading and Q/A sessions for the course.
OTHER PROFESSIONAL EXPERIENCE
Technical consultant, Fulbright and Jaworski, LLP. December 2004 to November 2005.
Reviewed documents in patent infringement lawsuit regarding cdma2000 technology,
summarized findings, and aided in preparing expert witness for trial.
Software design engineer, ViaSat, Inc. June 2004 to August 2004. Implemented
convolutional encoding / decoding scheme on a TI DSP for use in a real-time satellite
communication system, simulated data transmission using the designed encoder /
decoder, and tested / characterized performance.
HONORS AND AWARDS
2007 Hershel M. Rich Outstanding Invention Award
2005 National Science Foundation Graduate Fellowship Honorable Mention
2004-2005 Texas Instruments Graduate Fellowship
2004 ECE Department Best Senior Project Award
2001-2004 L.J. Walsh Scholarship, George R. Brown School of Engineering
PROFESSIONAL AFFILIATIONS AND ACTIVITIES
Member: Institute of Electrical and Electronics Engineers (IEEE)
Society for Industrial and Applied Mathematics (SIAM)
Eta Kappa Nu
Tau Beta Pi
Reviewer: IEEE Transactions on Information Theory
IEEE Transactions on Signal Processing
IEEE Transactions on Image Processing
IEEE Journal of Selected Topics in Signal Processing
IEEE Transactions on Aerospace and Electronic Systems
Journal of the Royal Statistical Society: Series B
Neurocomputing
IEEE International Symposium on Information Theory (ISIT)
European Signal Processing Conference (EUSIPCO)
Editor: Rejecta Mathematica
TEACHING EXPERIENCE
2004-2007 Course assistant – graded for ELEC 301, ELEC 430, and ELEC 431
2006-2007 Teaching Fellow for ELEC 301 (Introduction to Signals and Systems)
2003 Course assistant – led Q&A sessions for ELEC 301
2003 Course assistant – led Q&A sessions for ACCO 305
REFEREED JOURNAL PUBLICATIONS
R.G. Baraniuk, M.A. Davenport, R.A. DeVore, and M.B. Wakin, “A simple proof of the
restricted isometry property for random matrices,” Constructive Approximation, 28
(3) pp. 253—263, December 2008.
M.F. Duarte, M.A. Davenport, D. Takhar, J.N. Laska, T. Sun, K. Kelly, and R.G.
Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal
Processing Magazine, 25 (2) pp. 83—91, March 2008.
C.D. Scott and M.A. Davenport, “Regression level set estimation via cost-sensitive
classification,” IEEE Transactions on Signal Processing, 55 (6) pp. 2752—2757, June
2007.
JOURNAL PREPRINTS
M.A. Davenport, R.G. Baraniuk, and C.D. Scott, “Tuning support vector machines for
minimax and Neyman-Pearson classification,” Rice University ECE Technical
Report TREE 0804, August 2008.
REFEREED CONFERENCE PUBLICATIONS
M.A. Davenport, P.T. Boufounos, and R.G. Baraniuk, “Compressive domain interference
cancellation,” in Proc. Workshop on Signal Processing with Adaptive Sparse
Structured Representations (SPARS), Saint-Malo, France, April 2009.
M.F. Duarte, M.A. Davenport, M.B. Wakin, J.N. Laska, D. Takhar, K.F. Kelly, and R.G.
Baraniuk, “Multiscale random projections for compressive classification,” in Proc.
IEEE International Conference on Image Processing (ICIP), San Antonio, Texas,
September 2007.
M.A. Davenport, R.G. Baraniuk, and C.D. Scott, “Minimax support vector machines,” in
Proc. IEEE Workshop on Statistical Signal Processing (SSP), Madison, Wisconsin,
August 2007.
M.A. Davenport, R.G. Baraniuk, and C.D. Scott, “Learning minimum volume sets with
support vector machines,” in Proc. IEEE International Workshop on Machine
Learning for Signal Processing (ICASSP), Maynooth, Ireland, September 2006.
M.A. Davenport, R.G. Baraniuk, and C.D. Scott, “Controlling false alarms with support
vector machines,” in Proc. IEEE International Conference on Acoustics, Speech, and
Signal Processing (ICASSP), Toulouse, France, May 2006.
M.F. Duarte, M.A. Davenport, M.W. Wakin, and R.G. Baraniuk, “Sparse signal detection
from incoherent projections,” in Proc. IEEE International Conference on Acoustics,
Speech, and Signal Processing (ICASSP), Toulouse, France, May 2006.
INVITED CONFERENCE PUBLICATIONS
M.A. Davenport, M.F. Duarte, M.B. Wakin, J.N. Laska, D. Takhar, K.F. Kelly, and R.G.
Baraniuk, “The smashed filter for compressive classification and target
recognition,” in Proc. Computational Imaging V at SPIE Electronic Imaging, San Jose,
California, January 2007.
SELECTED REPORTS
M.A. Davenport, C. Hegde, M.F. Duarte, and R.G. Baraniuk, “A theoretical analysis of
joint manifolds,” Rice University ECE Technical Report TREE 0901, January 2009.
M.A. Davenport, M.B. Wakin, and R.G. Baraniuk, “Detection and estimation with
compressive measurements,” Rice University ECE Technical Report TREE 0610,
November 2006.
M.S. THESIS
M.A. Davenport, “Error control for support vector machines,” M.S. thesis, ECE Dept.,
Rice University, April 2007.
PATENTS
R.G. Baraniuk, D.Z. Baron, M.F. Duarte, S. Sarvotham, M.B. Wakin, M.A. Davenport,
“Method and Apparatus for Distributed Compressed Sensing.” US Patent No.
7,511,643. March 31, 2009.
R.G. Baraniuk, D.Z. Baron, M.F. Duarte, S. Sarvotham, M.B. Wakin, M.A. Davenport,
“Method and Apparatus for Distributed Compressed Sensing.” US Patent No.
7,271,747. September 18, 2007.
TALKS AND TUTORIALS
M.A. Davenport, M.F. Duarte, C. Hegde, and R.G. Baraniuk, “Joint manifold models for
collaborative inference,” Institute for Mathematics and Its Applications Hot Topics
Workshop: Multi-Manifold Data Modeling and Applications, Minneapolis, Minnesota,
October 2008.
M.A. Davenport, M.F. Duarte, R. Willett, and R.G. Baraniuk, “Sparse spectral
unmixing,” Computational Imaging VI at SPIE Electronic Imaging, San Jose,
California, January 2008.
M.A. Davenport, C. Hegde, M.B. Wakin, and R.G. Baraniuk, “Manifold-based
approaches for improved classification,” NIPS Workshop on Topology Learning,
Vancouver, Canada, December 2007.
C. Hegde, M.A. Davenport, M.B. Wakin, and R.G. Baraniuk, “Efficient machine learning
using random projections,” NIPS Workshop on Efficient Machine Learning,
Vancouver, Canada, December 2007.
M.A. Davenport, “Compressive signal processing,” MADALGO Summer School on Data
Stream Algorithms, Aarhus, Denmark, August 2007.
M.A. Davenport, “Compressive sensing: A new approach to data acquisition,”
Mitsubishi Electronic Research Labs (MERL), Boston, Massachusetts, July 2007.
M.A. Davenport, R.G. Baraniuk, and M.B. Wakin, “Scalable inference and recovery from
compressive measurements,” NIPS Workshop on Novel Applications of
Dimensionality Reduction, Vancouver, Canada, December 2006.
M.A. Davenport, “The Johnson-Lindenstrauss lemma meets compressed sensing,” Sparse
Approximation Workshop, Princeton, New Jersey, November 2006.