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Improving Representativeness in Non-Probability Surveys and Causal Inference with Regularized Regression and Post-Stratifiation

The proposed project has a broad aim of working with the increasing complexities of survey statistics with decreasing response rate. We focus specifically on non-probability samples (samples of convenience) due to their increasing popularity, but note that these non-probability samples are simply an extreme case of a probability based survey with high non-response, and so our methods could be expected to generalize.

RAPID: Flexible, Efficient, and Available Bayesian Computation for Epidemic Models

Decisions about coronavirus response are necessarily based on statistical models of prevalence, transmission risks, case fatality rate, projection of future spread of infection, and estimated effects of medical and social interventions. Much of this modeling and inference is being done using the Bayesian framework, an approach to statistics that is well suited to integration of information from different sources and accounting for uncertainty in predictions that can be input into decision analysis.

Collaborative Research: PPoSS: Planning: Scalable Systems for Probabilistic Programming

Statistical methods have had great successes for exploring data, making predictions, and solving problems in a wide range of problems. But in the world of big data, methods need to be scalable, so as to handle larger problems while modeling the real-world problems of messy and nonrepresentative data. The project?s novelties are developments in software and hardware facilitating full-stack integration of Bayesian inference to allow complex and realistic models to be fit to large datasets.

NSF Program on Fairness in Artificial Intelligence (AI) in Collaboration with Amazon (FAI)

NSF and Amazon are partnering to jointly support computational research focused on fairness in AI, with the goal of contributing to trustworthy AI systems that are readily accepted and deployed to tackle grand challenges facing society. Specific topics of interest include, but are not limited to transparency, explainability, accountability, potential adverse biases and effects, mitigation strategies, validation of fairness, and considerations of inclusivity. Funded projects will enable broadened acceptance of AI systems, helping the U.S.

Deadline: 

Monday, July 13, 2020

Uncommon Methods & Metrics

A primary data collection initiative to uncover how entrepreneurial ecosystems affect entrepreneurs

Deadline: 

Tuesday, July 11, 2017

CI-SUSTAIN: Stan for the Long Run

Stan is a software package that transforms scientific discovery by allowing scientists to quickly and easily explore, evaluate, and refine rich scientific hypotheses tailored to their particular research question and data collection mechanism. For computational reasons, analyses of data (big or otherwise) have tended to be simple and focused more on the difficulties of manipulating the data than on realistic scientific models.

Multidisciplinary Research Program of the University Research Initiative

This funding opportunity announcement includes topics of interest to the Army Research Office, the Air Force Office of Scientific Research, and the Office of Naval Research.

Deadline: 

Monday, May 18, 2020

Smart and Connected Communities

Cities and communities in the U.S. and around the world are entering a new era of transformational change, in which their inhabitants and the surrounding built and natural environments are increasingly connected by smart technologies, leading to new opportunities for innovation, improved services, and enhanced quality of life.

Deadline: 

Tuesday, August 6, 2019

Innovations at the Nexus of Food, Energy and Water Systems (INFEWS)

The overarching goal of INFEWS is to catalyze well-integrated interdisciplinary and convergent research to transform scientific understanding of the FEW nexus (integrating all three components rather than addressing them separately), in order to improve system function and management, address system stress, increase resilience, and ensure sustainability. The NSF INFEWS initiative is designed specifically to attain the following goals:

Deadline: 

Wednesday, September 26, 2018

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