Introducing the Moore Foundation's Data Driven Discovery (DDD) Investigators

Note: the source data for this is available on github at https://github.com/ctb/dddi

Today, the Moore Foundation announced that they have selected fourteen Moore Data Driven Discovery Investigators.

In reverse alphabetical order, they are:


Dr. Ethan White, University of Florida

Proposal: Data-intensive forecasting and prediction for ecological systems

Source code repository: https://github.com/weecology

Google Scholar: http://scholar.google.com/citations?user=pHmra8cAAAAJ&hl=en

ImpactStory: https://impactstory.org/EthanWhite

Blog: http://jabberwocky.weecology.org/

Twitter: @ethanwhite


Dr. Laura Waller, UC Berkeley

Source code repository: https://github.com/Waller-Lab/CalOptrics


Dr. Matt Turk, University of Illinois at Urbana-Champaign

Proposal: Changing How We Conduct Inquiry

Source code repository: http://bitbucket.org/MatthewTurk/

Google Scholar: http://scholar.google.com/citations?user=QTmv2p0AAAAJ&hl=en

Blog: https://plus.google.com/+MatthewTurk

Twitter: @powersoffour


Dr. Blair D. Sullivan, North Carolina State University

Proposal title: Enabling Science via Structural Graph Algorithms

Source code repository: https://github.com/bdsullivan/

Google Scholar: http://scholar.google.com/citations?user=oZBtvZMAAAAJ&hl=en&oi=ao

Twitter: @BlairDSullivan


Dr. Matthew Stephens, University of Chicago

Proposal title: Gene Regulation and Dynamic Statistical Comparisons

Source code repository: https://github.com/stephens999

Google Scholar: http://scholar.google.com/citations?user=qOQFhUkAAAAJ&hl=en

Blog: http://randomdeviation.blogspot.com/

Twitter: @mstephens999


Dr. Amit Singer, Princeton University

Proposal title: Maximum Likelihood Estimation by Semidefinite Programming: Application to Cryo-Electron Microscopy

Google Scholar: http://scholar.google.com/citations?user=h67w8QsAAAAJ&hl=en


Dr. Kimberly Reynolds, UT Southwestern

Proposal title: Decoding the Genome: Finding Effective Variables from Evolutionary Ensembles

Google Scholar: http://scholar.google.com/citations?user=6bWFU7MAAAAJ&hl=en&oi=ao


Dr. Chris Re, Stanford

Google Scholar: http://scholar.google.com/citations?user=DnnCWN0AAAAJ&hl=en


Dr. Laurel Larsen, UC Berkeley

Proposal title: Developing the informationscape approach to environmental change detection.


Dr. Carl Kingsford, Carnegie Mellon University

Proposal title: Lightweight Algorithms for Petabase-scale Genomics

Google Scholar: http://scholar.google.com/citations?user=V_cvqKcAAAAJ

Twitter: @ckingsford


Dr. Jeffrey Heer, U. Washington Seattle

Proposal: Interactive Data Analysis

Google Scholar: http://scholar.google.com/citations?user=vlgs4G4AAAAJ

Twitter: @jeffrey_heer


Dr. Casey Greene, Dartmouth

Proposal title: Learning the context of publicly available genome-wide data

Google Scholar: http://scholar.google.com/citations?user=ETJoidYAAAAJ&hl=en

Twitter: @GreeneScientist


Dr. C. Titus Brown, UC Davis

Proposal: Infrastructure for Data Intensive Biology

Source code repository: http://github.com/ged-lab/

Google Scholar: http://scholar.google.com/citations?user=O4rYanMAAAAJ

ImpactStory: https://impactstory.org/TitusBrown

Blog: http://ivory.idyll.org/blog/

Twitter: @ctitusbrown


Dr. Joshua Bloom, UC Berkeley

Proposal title: Efficient Data-Driven Astrophysical Inquiry with Machine Learning

Google Scholar: http://scholar.google.com/citations?user=fHkUYk0AAAAJ

Blog: http://5nf5.blogspot.com/

Twitter: @profjsb


--titus

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