Volunteer support for faculty research involving data science and data management
About the Collaboratory
The collaboratory is a pilot project for building a data analysis and collaboration network focused exclusively on smaller colleges and universities in New York State.
Leveraging the New York Six Liberal Arts Consortium (NY6) as a starting point, our intention is to build a cohort of statisticians and data librarians from regional colleges and universities, and from within the community. These experts will provide consultation and support in the following areas for researchers unaffiliated with a large research institution:
- Statistical methodology
- Secure and safe data storage
- Data mining and manipulation
This pilot project is funded by a 2018 Central NY Libraries Resources Council New Initiatives Grant.
Some examples of how the collaboratory is assisting research.
- Racial Biases in Officers’ Decisions to Frisk are Amplified for Black People Stopped among Groups
- Mp Fracking Twitter: Applying the Narrative Policy Framework to Fracking “Debates” in New York
Associate Professor, Biology & Mathematics, Colgate University
Mathematical modeling, deterministic and stochastic simulations, global optimization, sensitivity analysis, network analysis, supervised and unsupervised learning.
Associate Professor, University Libraries, Colgate University
Data visualizations, visual literacy, design thinking, digital pedagogies and technologies
Assistant Professor, Mathematics, Colgate University
Bayesian statistics, exploratory data analysis, count regression, moderated mediation, natural language processing (twitter data)
Head of Research & Instruction, Associate Professor, Libraries, Colgate University
Research data management, discovery, curation
Associate Professor, Mathematics, Hamilton College
Non parametric and semi parametric models, variable selection
Assistant Professor, Mathematics, Hamilton College
Mathematical modeling, uncertainty quantification, Bayesian statistics, high-performance computing
Professor of Statistics, Mathematics, Computer Science and Statistics, St. Lawrence University
Applied statistics, statistical methodology, sports, bioauthentication, classification performance
Associate Professor, Mathematics, Statistics & Computer Science, Le Moyne College
Exploratory data analysis, multiple regression, logistic regression, Poisson regression, one-way and two-way ANOVA, ANCOVA, MANOVA, MANCOVA, principal components analysis, factor analysis.
Assistant Professor, Mathematics, SUNY-Brockport
Count regression, cluster analysis, exploratory data analysis, applied statistics
- Caio Rodrigues Faria Brighenti '20, Peace & Conflict Studies
- Chau Pham '22, Computer Science
- Jake Scott ’20, Economics
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