Jacob Foster, UCLA
February 03, 2017
Searle 240

Made to Know: Science as the Social Production of Collective Intelligence
Speaker: Jacob Foster, UCLA

Feng "Bill" Shi, University of Chicago
January 22, 2016
Searle 240, 5735 S. Ellis Ave.

Computation Institute Presentation - Data Lunch Seminar (DLS)

Joe Walsh, Eamon Duede, & TBA
January 06, 2016
Searle 240, 5735 S. Ellis Ave.

Applying Data Science!

In The News
Chronicle of Higher Education

In two recent studies, CI Senior Fellows James Evans and Andrey Rzhetsky built a network of millions of papers to ask an important question: is scientific research living up to its potential?  Their analysis, conducted with UCLA's Jacob Foster and CI Director Ian Foster, found that science increasingly explores more incremental and conservative questions, avoiding the

Tim Weninger, University of Notre Dame
November 20, 2015
Searle 240A

Abstract: In this talk we present current and ongoing work about how humans create networks of information and navigate those networks in the pursuit of knowledge. First, we will d

Press Release

Institutional and cultural pressures lead scientists to avoid risk-taking and choose inefficient research strategies, two new University of Chicago papers conclude. Despite increased opportunities for groundbreaking experiments, most scientists choose conservative research strategies to reduce personal risk, which makes collective discovery slower and more expensive.

Press Release

A new analysis of nearly 4 million scientific articles finds that research is disproportionately focused on diseases that primarily afflict wealthy countries. Correspondingly, less research attention is given to diseases of the developing world, increasing global health disparities, concludes the study from the CI's Knowledge Lab, published in PLoS ONE.

Press Release

The march of science is stumbling and easily sidetracked, fraught with bias, fads and dead ends. A new research initiative based at the University of Chicago and the Computation Institute will use the latest computational tools to scrutinize this imperfect path and better understand how knowledge was and is created. Such understanding could transform the process of research, calling out past missteps while revealing unanticipated new directions for the future.