Rebecca Willett

Research Interests:

My research interests include network and imaging science with applications in medical imaging, wireless sensor networks, astronomy, and social networks. One central theme of my research is data-starved inference for point processes -- the development of statistically robust methods for analyzing discrete events, where the discrete events can range from photons hitting a detector in an imaging system to groups of people meeting in a social network. When the number of observed events is very small, accurately extracting knowledge from this data is a challenging task requiring the development of both new computational methods and novel theoretical analysis frameworks. This body of research has led to important insights into the performance of compressed sensing in optical systems, tools for tracking dynamic meeting patterns in social networks, predictions of future IED locations in Afghanistan, and novel sparse Poisson intensity reconstruction algorithms for night vision and medical imaging.

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.

Recent Publications: (More Publications)

• E. Wang, J. Silva, R. Willett, and L. Carin, Time-Evolving Modeling of Social Networks, ICASSP (2011) [abs]
• C. Horn and R. Willett, Online anomaly detection with expert system feedback in social networks, ICASSP (2011) [abs]
• R. Willett, Errata: Sampling Trajectories for Sparse Image Recovery (2011) [abs]
• M. Raginsky, N. Kiarashi, and R. Willett, Decentralized online convex programming with local information, Proceedings of American Control Conference (2011) [abs]
• E. Wang, J. Silva, R. Willett, L. Carin, Dynamic Relational Topic Model for Social Network Analysis with Noisy Links, Statistical Signal Processing Workshop 2011 (2011)