Deep Text-Mining for Cancer and Disease

Ishanu Chattopadhyay, Conte Center for Computational Neuropsychiatric Genomics; James Evans, Knowledge Lab
May 20, 2015
Searle 240A, University of Chicago & Webcast via BlueJeans

Abstract: We will explore the nature and limits of mining and linking textual information from scientific publications, and the possibilities that it unlocks for understanding: (1) the rise of scientific and biomedical fields; (2) the firmness of existing scientific knowledge; and (3) the “gaze” of scientific investigation, the dynamics of discovery, and their implication for science and health policy.

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The Power in Patterns: How Big Data is Improving Patient Care

Ian Foster, Jonathan Silverstein, Rayid Ghani
May 18, 2015
MATTER, 222 W Merchandise Mart Plaza #1230, Chicago, IL

Big Data has revolutionized the business world and is starting to have the same impact in healthcare. Using sophisticated analytical tools, hospitals and health systems are interpreting massive amounts of patient data to help them improve care and make it more efficient and cost effective. Such analysis is helping caregivers identify patients who might be at risk for certain ailments, allowing for earlier intervention, and improving patient safety by recognizing potential vulnerabilities in the care continuum.

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What Academia Can Learn From Open Source

Arfon Smith, Github
May 15, 2015
University of Chicago, Searle 240A, 5735 S. Ellis Ave. & Webcast via BlueJeans

What academia can learn from open source 

Abstract: Practices vary between scientific domains but all too often the sharing of research software is done on an ad hoc basis between individuals and with little thought about the wider community. With code and computation encapsulating an ever-increasing fraction of research activity, now more than ever there is a need to develop a culture of sharing and reuse similar to that found in open source communities.

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Spatial Data Science in a CyberGIS Era

Luc Anselin, PhD, Regents' Professor and Walter Isard Chair; Director, GeoDa Center for Geospatial Analysis and Computation; School of Geographical Sciences and Urban Planning, Arizona State University
May 11, 2015
The University of Chicago, Searle 240A, 5735 S. Ellis Ave.

This talk focuses on a number of important computational aspects associated with the implementation of spatial data science functionality in software. It provides a brief overview of the evolution of software, particularly my own efforts which include SpaceStat in the 1990s and GeoDa and PySAL in the more recent past. Particular attention is paid to our current work on moving such capability from the desktop to a cyberinfrastructure environment, or CyberGIS.

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