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Data Theory and Analysis

a)    Danielle Bassett Complex Systems, Network Science, Computational Neuroscience, Systems Biology, Dynamical Systems, Soft Materials, Behavioral Network Science.

b)    Larry Brown Statistical decision theory, Statistical inference, Nonparametric function estimation, Foundations of statistics, Sampling theory (census data), Empirical queueing science.

c)    Andreas Buja Multidimensional Scaling, Multivariate Analysis, Statistical Inference after Model Selection, High-Dimensional Data Visualization.

d)   Tony Cai High dimensional statistical inference, Nonparametric function estimation, Large-scale multiple testing, Wavelet methodology and applications, Functional data analysis, Statistical decision theory.

e)    Dean Foster Variable selection,Learning models,Evolution and games.

f)    Ed George Hierarchical modeling, model uncertainty, shrinkage estimation, treed modeling, variable selection, wavelet regression.

g)   Phil Gressman Harmonic analysis and geometry.

h)   Michael Kearns Machine learning, algorithmic game theory, social networks, computational finance, and artificial intelligence, and applications of machine learning to finance, spoken dialogue systems, and other areas.

i)    Junhyong Kim Evolution of gene regulation and developmental systems, whole-genome expression regulations and evolution of the transcriptome, dynamics of whole-genome  gene expression, protein structure evolution,           phylogenetic estimators, comparative genomics and molecular evolution.

j)    Hongzhe Li Statistical, probabilistic, and computational methods for genetic and genomic data analysis, bioinformatics and computational biology.

k)   Phil Nelson Physics of artificial biomembranes, biopolymers such as DNA, and other "soft" condensed matter systems.

l)    Victor Preciado

m)    Alexander Rakhlin Applied probability, machine learning, optimization, sequential prediction, statistical learning theory.

n)  Aaron Roth Algorithmic foundations of data privacy and game theory.

o)  Dylan Small  Applications of statistics to public health, design and analysis of experiments and observational studies for comparing treatments, longitudinal data, measurement error, medicine and economics.

p)  Lyle Ungar Scalable machine learning and text mining methods, including clustering, feature selection, and semi-supervised and multi-task learning for natural language, psychology, and medical research.

q)  Abraham Wyner Baseball, boosting, data compression, entropy, information theory, probabilistic modeling, temperature reconstructions.