Partial list of research topics
Data visualization and analytics
High-speed visualization of high-dimensional datasets; data representation, extraction, integration and transformation; real-time visual interaction; spatio-temporal data mining
Online streaming and sketching
Algorithm paradigms for massive datasets (streaming, online, randomized); scalability; filtering; anomaly detection; data structures for fast computation of statistics; database enabled machine learning tools; computing environments and programming models (GPU’s, cloud computing, custom chips)
Large-scale optimization
Convex optimization (sparse modeling and compressed sensing, matrix completion); online optimization (streaming data, on-line learning, control theory); distributed optimization (parallel and GPU computation, data fusion); machine learning; high-dimensional models
Inference
Dimension reduction for high-dimensional data (feature selection, sub-sampling and screening, sparse PCA); predictive inference and multiple testing (false discovery rates, uncertainty in prediction); high-dimensional MCMC methods for posterior inference (particle filters, hybrids with optimization methods)
Imaging
Rapid registration and segmentation (GPU’s, distributed computing); multiple testing and inference for large-scale imaging data (sky surveys, satellite images, false discovery rate with dependence); dynamic imaging (streaming data, spatio-temporal models)
Systems and architectures
Reliability; resilience; probabilistic computing, multiple precision; real-time methods; variable data flows; hardware platforms
High-energy physics
Reconstruction and analysis of particle collisions from the LHC; pattern recognition and parameter extraction; simulations to estimate error rates; parameter estimation for large numbers of parameters; maximum likelihood estimators
Astronomy
Statistics on remote resources; computations on special purpose architectures and GPUs; communication avoiding methods; randomized and online algorithms; detection and classification of transient events and outliers; Bayesian inference and machine learning; high dimensional models with empirical priors; non-parametric models; visualization of large high-dimensional datasets
Environment and climate
Production, validation, processing, distribution and integration of data; data fusion and remote sensing; algorithms for large distributed datasets; spatial or spatio-temporal statistics
Schedule and Supporting Media
Sunday, September 9, 2012
Radisson RTP
Monday, September 10, 2012
Radisson RTP
Tuesday, September 11, 2012
Radisson RTP
Wednesday, September 12, 2012
Radisson RTP