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Frontiers in Massive Data Analysis (2013) / Chapter Skim
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Appendix B: Biographical Sketches of Committee Members
Pages 171-176

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From page 171...
... He developed new graphical model architectures that have had impact in various applied fields, including bioinformatics, computational vision, speech, natural language processing and information retrieval, and has contributed to the development of a new framework for inference in graphical models based on variational representations of probability distributions. Another area of focus has been nonparametric inference, including both Bayesian nonparametrics, where he developed new models based on the area of stochastic processes known as completely random measures, and frequentist nonparametrics, where he focused on kernel machines, spectral methods, dimension reduction and classification.
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From page 172...
... Her research combines cognitive science, social networks, and computer science to address complex social and organizational problems. Her specific research areas are dynamic network analysis, computational social and organization theory, adaptation and evolution, text mining, and the impact of telecommunication technologies and policy on communication, information diffusion, disease contagion, and response within and among groups, particularly in disaster or crisis situations.
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From page 173...
... Siebel Professor of Computer Science at the University of California, Berkeley, specializing in large-scale data management applications and infrastructure.
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From page 174...
... His current research focuses on applied problems in biology and genomics, medicine, and industry, in particular data mining, prediction, and classification problems. PIOTR INDYK is a professor in the Department of Electrical Engineering and Computer Science at Massachusetts Institute of Technology (MIT)
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From page 175...
... His research interests are algorithmic and statistical aspects of modern large-scale data analysis; design and analysis of algorithms for matrix, graph, and regression problems; statistical data analysis in large-scale scientific and Internet applications; applications to the analysis of large social and information networks; applications to DNA microarray and single nucleotide polymorphism data; and randomized algorithms for large linear algebra problems. Much of his current research focuses on geometric network analysis, developing a ­ pproximate computation and regularization methods for large informatics graphs; applications in large social and information networks; and statistical data analysis of extremely large data sets.
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From page 176...
... YORAM SINGER is a senior research scientist at Google, Inc. Before joining Google, he was an associate professor at the School of Computer Science and Engineering of Hebrew University of Jerusalem, and before that he was a member of the technical staff at AT&T-Research.
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Key Terms

  • electrical engineering
  • network analysis
  • hebrew university
  • mathematical statistics
  • graphical models

  • linear algebra
  • applied mathematics
  • natural language
  • information networks
  • statistical machine

  • models based
  • numerical analysis
  • randomized algorithms
  • massive data
  • technical staff

  • text mining
  • language processing
  • data mining
  • random variables
  • interdependent collections

  • physical data
  • piotr indyk
  • dynamic network
  • complex analysis
  • jet propulsion

  • people laboratory
  • applied fields
  • completely random
  • perform machine
  • complex social


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