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This section tends to lag in time! Please see CV for current list.


Theses


Highly-Selective Conferences


Preprints


Journal Papers


Other Peer-Reviewed Conferences, Symposia, and Workshops


Selected Invited Talks and Workshops

  • “Scalable Approaches to New Large-Scale Neuroscience,” IEEE Signal Processing Society, Silicon Valley Chapter, November 5, 2015.
  • “Scalable Inference of Neural Dynamical Systems,” 53rd Annual Allerton Conference on Communication, Control & Computing, October 3, 2015.
  • “Structured Estimation of Visual Receptive Fields,” Bay Area Vision Research Day (BAVRD), September 18, 2015.
  • “Inference for New Large-Scale Neuroscience,” Mining and Modeling of Neuroscience Data, CRCNS/MSRI Summer School, University of California, Berkeley, July 15, 2015.
  • “Inferring Structure in Large Neural Systems,” Mathematics & Statistics Department Seminar, Boston University, March 19, 2015.
  • “Inferring Structure in Large Neural Systems,” Data Seminar: Departments of Mathematics, Electrical Engineering & Biomedical Engineering, Duke University, March 13, 2015.
  • “Inferring Structure in Large Neural Systems,” Department of Statistics Seminar, University of California, Los Angeles, March 10, 2015.
  • “Inferring Structure in Large Neural Systems,” Applied Mathematics & Statistics Department Seminar, Johns Hopkins University, February 27, 2015.
  • “Inferring Structure in Large Neural Systems,” Applied Mathematics & Electrical Engineering Seminar, Harvard University, February 25, 2015.
  • “Inferring Structure in Large Neural Systems,” Applied Mathematics Seminar, University of Washington, February 19, 2015.
  • “Inferring Structure in Large Neural Systems,” Department of Mathematics and Statistics Seminar, University of San Francisco, February 10, 2015.
  • “Uncovering Structure in Neural Systems,” Information Theory and Applications Workshop, February 6, 2015.
  • Stanford Compression Forum, January 22, 2015.
  • “Scalable Identification for Structured Nonlinear Neural Systems,” Redwood Center for Theoretical Neuroscience Seminar, University of California, Berkeley, May 7, 2014.
  • “Scalable Identification for Structured Nonlinear Neural Systems,” ISL Big Data Seminar Series, Stanford University, April 10, 2014.
  • “Bayesian Inference of Sparse Neural Dynamical Systems,” Information Theory and Applications Workshop, University of California, San Diego, February 13, 2014.
  • “Scalable Identification for Structured Nonlinear Neural Systems,” University of California, Berkeley, Control Theory Seminar, February 3, 2014.
  • “Scalable Identification for Structured Complex Nonlinear Systems,” University of California, San Diego, ECE Seminar, January 30, 2014.
  • Co-organizer, International Workshop on High-Dimensional Statistical Inference in the Brain, Neural Information Process. Symp. (NIPS), 2013 (Lake Tahoe, NV, Dec 5-10).
  • “Learning Sparse Priors in Approximate Message Passing,” Information Theory and Applications Workshop, University of California, San Diego, February 13, 2013.
  • “Neural Connectivity and Receptive Field Estimation via Hybrid Message Passing,” Information Theory and Applications Workshop, University of California, San Diego, February 6, 2012.
  • “Neural Connectivity and Receptive Field Estimation via Hybrid Message Passing,” Mathematical EE Seminar, University of California, Santa Cruz. January 27, 2012.
  • ”Sparsity: Algorithms and Applications in Neuroscience,” Applied Mathematics and Mathematical Biology Seminar, Claremont Graduate University, January 25, 2012.
  • “Exploiting Sparsity: Algorithms and Applications,” Electrical and Computer Engineering Seminar, University of California, Davis, November 14, 2011.
  • “Generalized Approximate Message Passing and Applications in Neural Receptive Field Estimation and Connectomics,” Redwood Center for Theoretical Neuroscience, University of California, Berkleley, June 8, 2011.
  • “Algorithms for High-Dimensional Inference: Analysis and Applications,” University of California, Davis Department of Electrical and Computer Engineering, May, 2011.
  • “Algorithms for High-Dimensional Inference: Analysis and Applications,” University of Massachusetts Department of Electrical and Computer Engineering, April 20, 2011.
  • “Algorithms for High-Dimensional Inference: Analysis and Applications,” University of Florida Department of Electrical and Computer Engineering, April 20, 2011.
  • “Compressed Sensing to the Limits: Bounds, Algorithms, andWireless Applications,” University of Michigan Electrical Engineering and Computer Science Seminar, March 31, 2009.
  • “Sparsity Recovery: Limits, Algorithms and Wireless Applications,” DIMACS/DyDAn Working Group on Streaming, Coding, and Compressive Sensing: Unifying Theory and Common Applications to Sparse Signal/Data Analysis and Processing, New Brunswick, NJ, March 25–26, 2009. (By invitation only workshop speaker and participant.)
  • “Sparsity Pattern Recovery: Precisely Contrasting Thesholding, Lasso, and Maximum Likelihood,” University of California at San Diego Information Theory and Applications Workshop, February 8–13, 2009.
  • “Random Access Channels and Sparsity Detection,” University of California at San Diego Information Theory and Applications Workshop, February 8–13, 2009.
  • American Institute of MathematicsWorkshop on Frames for the FiniteWorld: Sampling, Coding, and Quantization, August 18–22, 2008 (invited participant).
  • Banff International Research Station Workshop on Mentoring for Engineering Academia II, July 22–27, 2007 (invited participant), Banff, Alberta, Canada.
  • “Compressed Sensing as a Source Coding Technique,” 2007 von Neumann Symposium on Sparse Representation and High-Dimensional Geometry, July 8–12, 2007, Snowbird, UT.
  • “On Encoding with a Codebook of Subspaces,” University of California at San Diego Information Theory and Applications Workshop, January 29, 2007.
  • “Rate-Distortion Performance of Sparse-Signal Coding with Random Measurements,” SIAM Conference on Imaging Science, May 15, 2006, Minneapolis, MN.
  • University of California at San Diego Workshop on Information Theory and Its Applications, February 6–10, 2006 (invited participant).
  • “Estimation and Robust Communication of Signals with Markovian Losses,” ´ Ecole Polytechnique F´ed´erale de Lausanne, Computer and Communication Sciences Department, July 14, 2005, Lausanne, Switzerland.
  • “Estimation with Markovian Dynamics and Sparseness,” University of California, Berkeley, Networking/Communication/DSP Seminar, April 20, 2005, Berkeley, CA.
  • UCLA Institute for Pure and Applied Mathematics (IPAM) Program on Multiscale Geometry and Analysis in High Dimensions, Fall 2004.
  • PAESMEM/Stanford School of Engineering Workshop on Mentoring in Engineering, June 21–22, 2004.
  • “Sparseness from Redundancy: Denoising Methods and Bounds,” University of Cambridge, Department of Engineering, Signal Processing Seminar, October 2, 2003, Cambridge, UK.
  • “Wavelet Denoising by Recursive Cycle Spinning,” DIMACSWorkshop on Source Coding and Harmonic Analysis, May 9, 2003, New Brunswick, NJ.