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| Conference on Research in Computational Statistics (CRiS) | |
|---|---|
| Name | Conference on Research in Computational Statistics (CRiS) |
| Abbreviation | CRiS |
| Established | 2010 |
| Frequency | Annual |
| Discipline | Computational Statistics |
Conference on Research in Computational Statistics (CRiS) is an annual scientific meeting that gathers researchers in Machine learning, Statistics, Computer science, Applied mathematics, and Data science to present advances in algorithmic inference, simulation, and high-performance computation. The meeting attracts participants from institutions such as Massachusetts Institute of Technology, Stanford University, University of Cambridge, University of Oxford, and University of California, Berkeley and often features collaborations with organizations like Google, Microsoft Research, Amazon Web Services, and NVIDIA Corporation. CRiS serves as a nexus connecting communities represented at conferences such as NeurIPS, ICML, Royal Statistical Society, Joint Statistical Meetings, and International Conference on Machine Learning.
CRiS focuses on methodological and computational advances in Bayesian statistics, Monte Carlo methods, Markov chain Monte Carlo, Variational inference, Optimization, and High performance computing. The conference highlights intersections with applications from laboratories and centers including Los Alamos National Laboratory, Lawrence Berkeley National Laboratory, Argonne National Laboratory, CERN, and industry partners like IBM Research and Facebook AI Research. Typical sessions mirror program structures from International Conference on Very Large Databases, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, and SIAM Conference on Computational Science and Engineering.
CRiS was founded in 2010 by faculty and researchers affiliated with Imperial College London, ETH Zurich, University of Washington, and Columbia University to bridge gaps between communities represented by Royal Statistical Society, Institute of Mathematical Statistics, Association for Computing Machinery, and Society for Industrial and Applied Mathematics. Early organizers included scholars who had presented at Bernoulli Society meetings, International Biometric Society symposia, and European Meeting of Statisticians. The conference expanded during the 2010s alongside growth at NeurIPS, ICML, and AAAI Conference on Artificial Intelligence, adding workshops inspired by Workshop on Bayesian Nonparametrics, Workshop on Probabilistic Programming, and collaborative programs modeled on CERN Openlab exchanges.
Topics encompass algorithmic foundations such as Hamiltonian Monte Carlo, Gibbs sampling, Sequential Monte Carlo, Stochastic gradient Langevin dynamics, and Expectation–maximization algorithm. Computational themes include implementations for GPUs, TPUs, HPC, and distributed frameworks used by Google Cloud Platform, Microsoft Azure, and Amazon Web Services. Application areas frequently addressed mirror domains represented at National Institutes of Health, European Research Council, World Health Organization, NASA, and European Space Agency including genomics workflows discussed at Cold Spring Harbor Laboratory, climate modeling related to Intergovernmental Panel on Climate Change, and financial analytics connected to New York Stock Exchange research groups.
CRiS is typically organized by a rotating steering committee with representatives from universities like Princeton University, University of Chicago, University of Toronto, and McGill University and institutional partners including National Science Foundation, Engineering and Physical Sciences Research Council, and Horizon 2020. The governance model draws on precedents set by Conference on Neural Information Processing Systems and International Conference on Machine Learning with program chairs, local arrangements chairs, and an international program committee that includes editors from journals such as Journal of the Royal Statistical Society, Annals of Statistics, Journal of Machine Learning Research, and IEEE Transactions on Pattern Analysis and Machine Intelligence. Sponsorship often comes from corporations like Intel, AMD, NVIDIA Corporation, and funding agencies like European Research Council.
Accepted papers are published in conference proceedings and archived with indexing services used by ACM Digital Library, IEEE Xplore, and arXiv. Special issues have been coordinated with journals including Journal of Computational and Graphical Statistics, Statistics and Computing, Biometrika, Journal of Machine Learning Research, and Nature Methods. Workshops and tutorials have produced edited volumes modeled on those from Springer, Elsevier, and Oxford University Press collections. Reproducibility initiatives at CRiS echo efforts by Open Science Framework, ReproZip, and ICLR reproducibility challenges.
Plenary and keynote speakers have included faculty and researchers affiliated with Yale University, Harvard University, California Institute of Technology, University of Pennsylvania, Duke University, and industry labs such as DeepMind, OpenAI, Google DeepMind, and Microsoft Research. Award programs recognize early-career investigators, best paper awards, and software prizes, drawing inspiration from honors like the Rothschild Prize, Turing Award, Fields Medal, and discipline-specific awards such as the R. A. Fisher Award and COPSS Presidents' Award. Recipients often have parallel recognition from organizations like Royal Society, National Academy of Sciences, and Academia Europaea.
CRiS has influenced methodological adoption in projects at CERN, clinical trials groups at National Institutes of Health, and computational pipelines at Broad Institute. Its tutorials and software sessions have accelerated uptake of libraries from TensorFlow, PyTorch, Stan, JAGS, BUGS, and frameworks used in collaborations with Amazon Web Services. The conference has been cited in policy and research planning documents from agencies such as National Science Foundation, European Commission, and UK Research and Innovation and discussed at partner meetings including G7 Science Ministers' Meeting and forums like World Economic Forum. Critics have compared CRiS to larger venues including NeurIPS and ICML regarding selectivity and scale, while proponents highlight its focused intersection of computation and statistical theory.
Category:Computational statistics conferences