Nima Noorshams

PhD Candidate
Electrical Engineering and Computer Sciences
University of California, Berkeley

Contact: 264 Cory Hall, Berkeley, CA, 94720.
nshams (at) eecs (dot) berkeley (dot) edu



About Me
I am currently pursuing my PhD degree in Electrical Engineering and Computer Sciences at the University of California, Berkeley, under the supervision of Prof. Martin Wainwright. In March 2013, I obtained a master's degree from the Statistics department. Prior to that, in summer of 2007, i received my B.Sc. degree in Electrical Engineering from the Sharif University of Technology.

Research Interests
My research interest is primarily in statistical signal processing, machine learning, graphical models, and optimization. More specifically, I have been working on theoretically sound, low-complexity alternatives to some well known data inference algorithms such as belief propagation and gossip type averaging.

Publications
  • Nima Noorshams, and Martin J. Wainwright, "Stochastic Belief Propagation: A Low-Complexity Alternative to the Sum-Product Algorithm''. IEEE Transaction on Information Theory, 59(4):1981-2000, April 2013. arxiv, PDF.

  • Nima Noorshams, and Martin J. Wainwright, "Belief Propagation for Continuous State Spaces: Stochastic Message-Passing with Quantitative Guarantees''. Submitted to the Journal of Machine Learning Research, December 2012. arxiv, PDF.

  • Nima Noorshams, and Martin J. Wainwright, "Quantized Stochastic Belief Propagation: Efficient Message-Passing for Continuous State Spaces''. In proceedings of the IEEE International Symposium on Information Theory, July 2012. PDF.

  • Nima Noorshams, and Martin J. Wainwright, "Non-Asymptotic Analysis of an Optimal Algorithm for Network-Constrained Averaging With Noisy Links''. IEEE Journal of Selected Topics in Signal Processing, 5(4):833-844, August 2011. arxiv, PDF.

  • Nima Noorshams, and Martin J. Wainwright, "Stochastic Belief Propagation: Low-Complexity Message-Passing with Guarantees''. In proceedings of the 49th Annual Allerton Conference on Communication, Control, and Computing, September 2011. PDF.

  • Sameer Pawar, Nima Noorshams, Salim El Rouayheb, and Kannan Ramchandran, "DRESS Codes for the Storage Cloud: Simple Randomized Constructions''. In proceedings of the IEEE International Symposium on Information Theory, August 2011. PDF.

  • Nima Noorshams, and Martin J. Wainwright, "Lossy Source Coding with Sparse Graph Codes: A Variational Formulation of Soft Decimation''. In proceedings of the 48th Annual Allerton Conference on Communication, Control, and Computing, September 2010. PDF.

  • Nima Noorshams, and Martin J. Wainwright, "A Near-Optimal Algorithm for Network-Constrained Averaging with Noisy Links''. In proceedings of the IEEE International Symposium on Information Theory, June 2010. PDF.

  • Nima Noorshams, Mehdi Malboubi, and Ahmad Bahai, "Centralized and Decentralized Cooperative Spectrum Sensing in Cognitive Radio Networks: A Novel Approach''. In proceedings of the 11th IEEE International Workshop on Signal Processing Advances in Wireless Communications, June 2010. PDF.

  • Nima Noorshams, Massoud Babaie-Zadeh, and Christian Jutten, "Estimating the Mixing Matrix in Sparse Component Analysis Based on Converting a Multiple Dominant to a Single Dominant Problem''. In proceedings of the 7th International Conference on Independent Component Analysis and Signal Separation, September 2007. PDF.

Work/Teaching Experiences
  • Interim engineering intern, Qualcomm New Jersey research center systems group, summer 2012.

  • Graduate student instructor for the course signals and systems at the University of California Berkeley, Spring 2011.

  • Graduate student instructor for the course probability and random processes at the University of California Berkeley, Spring 2009.

  • Teaching assistant for the course discrete-time signal processing at Sharif University of Technology, Spring 2006.

Courses
  • Electrical engineering: Random Processes in Systems, Linear System Theory, Convex Optimization, Information Theory, Error Control Coding, Fundamentals of Wireless Communications, Neural Computations, Applied Stochastic Processes.

  • Statistics: Statistical Learning Theory, Advanced Topics in Learning and Decision Making, Probability and Measure Theory (A & B), Theoretical Statistics (A & B), Statistical inference in High Dimensions.

Invited Talks
  • "Stochastic Belief Propagation: Low-Complexity Message-Passing with Guarantees'', talk at Asilomar Conference on Signal, Systems, and Computers, November 2011.