Rebecca Willett, Assistant Professor of Electrical & Computer Engineering
Rebecca Willett completed her PhD in Electrical and Computer Engineering at Rice University in 2005. In addition to studying at Rice, she has worked as a Fellow of the Institute for Pure and Applied Mathematics at UCLA, as a visiting researcher at the University of Wisconsin-Madison and the French National Institute for Research in Computer Science and Control (INRIA), and as a member of the Applied Science Research and Development Laboratory at GE Medical Systems (now GE Healthcare). She is the recipient of the National Science Foundation Graduate Research Fellowship , the Rice University Presidential Scholarship, and the Society of Women Engineers Caterpillar Scholarship.
| Office Location: | FCIEMAS 3463 |
| Office Phone: | +1 919 660 5544 |
| Email Address: |   |
| Web Page: | http://www.ee.duke.edu/~willett |
Teaching (Fall 2008):
- ECE 189.01, DIG IMAGE/MULTIDIM PROCESSING
- Education:
PhD Rice University 2005 MS Rice University 2002 BSE Duke University 2000
- Specialties:
-
Sensing and Sensor Systems
Homeland Security
Medical Imaging
K-12 Education in Science & Mathematics
Signal Processing
Photonics
Distributed Systems
- Research Interests: Networking and Imaging Science
Current projects: Compressive Optical Sensor Design, Anomaly Detection in Sensor Networks, Activity Detection in fMRI, Hyperspectral Image Reconstruction for Astronomy and Multiphoton Microscopy
As the prevalence of sophisticated and inexpensive data collection technology increases, so does our need for accurate and efficient data transmission, storage, analysis, and interpretation. Critical applications such as medical imaging, astrophysics, bioinformatics, communication networks, data mining, and pattern recognition all hinge on our ability to process very large collections of data. The extraction of useful information from data which may be distorted, error riddled, corrupted, or partially irrelevant, or "information processing", is a fundamental challenge faced by diverse fields, from engineering and homeland security to advertising, search engine development, and environmental monitoring. Both my teaching and research are focused on fundamental methodological and theoretical aspects of information processing with a wide variety of important and exciting applications.
- Areas of Interest:
- Compressed Sensing
Photon-Limited Imaging
Network Anomaly Detection
Medical Imaging
Hyperspectral Imaging
Astronomical Signal Processing
- Keywords:
- poisson • wavelets • signal processing • compressed sensing • image processing • multiscale analysis • spectroscopy • optical sensors • superresolution • fMRI • astronomical signal processing
- Current Ph.D. Students
- Postdocs Mentored
- Maxim Raginsky (September, 2007 - present)
- Roummel Marcia (May, 2007 - present)
- Jorge Silva (February, 2007 - present)
- Recent Publications
(More Publications)
(search)
- J. Silva and R. Willett, Hypergraph-based anomaly detection in very large networks (Submitted, 2007)
- R. Willett, Multiscale intensity estimation for marked Poisson processes, in Proceedings IEEE Int. Conf. Acoust., Speech, Signal Processing (ICASSP) (2007)
- C. Scott and G. Bellala and R. Willett, Genearlization error analysis for FDR controlled classification, in Proceedings of IEEE Statistical Signal Processing Workshop (SSP) (2007)
- R. Willett and R. Nowak, Multiscale Poisson intensity and density estimation, IEEE Transactions on Information Theory, vol. 53 no. 9 (2007), pp. 3171-3187
- R. Willett, M. Gehm and D. Brady, Multiscale reconstruction for computational spectral imaging, in Proceedings of SPIE Electronic Imaging, Computational Imaging V (2007)
- Recent Grant Support
- Career: Data-Starved Inference on Point Processes, National Science Foundation, CCF-0643947, 2007/02-2011/01.
- Compressive Optical Systems- Theory, Devices, and Implementations, Rice University, R15391, 2006/05-2008/04.
- Discrete Event Data Analysis, Defense Advanced Research Projects Agency, HR0011-07-1-0030, 2007/04-2008/04.
- Large Area Coverage Optical Search-While-Track and Engage, Lockheed Martin Corporation, HR0011-06-C-0109, 2006/07-2006/12.