News for Media

Tuesday, July 28, 2020

One-stop collection and analysis with Archive-It and the Archives Unleashed Project

photo of Ian Milligan, Jimmy Lin, Nick Ruest and Jefferson Bailey

Suppose you’re an archivist, librarian, or historian who’s trying to document and preserve for posterity a narrative of the COVID-19 pandemic or the ongoing Black Lives Matters protests. You’ll naturally be gathering documents from the web, and with tools available today it won’t be difficult to accumulate thousands or even millions of relevant records. How can you make sure that a scholar down the road can actually use the material that you’ve collected?

Friday, May 29, 2020

Waterloo-based AI start-up Inductiv acquired by Apple

photo of Professor Ihab Ilyas

Waterloo-based Inductiv Inc., an AI start-up that uses machine learning to automate the task of identifying and correcting errors in data, has been bought by tech giant Apple.

Monday, May 11, 2020

DSG researchers use technology-assisted review to find effective treatments and procedures to mitigate COVID-19

photo of Maura R. Grossman and Gordon V. Cormack

Since the COVID-19 pandemic began, researchers and clinicians have rushed to understand the available treatments and procedures to mitigate this rapidly growing threat to human health. The sheer volume of studies published on COVID-19 — in countries spanning the globe — as well as lessons learned from prior epidemics and pandemics, simply cannot be gathered and assessed quickly enough using traditional manual methods during this time of crisis.

Tuesday, April 7, 2020

Professor Jimmy Lin and his colleagues create a new AI-powered search engine that makes it easier to find information in the fight against COVID-19

illustration of the SARS-Cov-2 virus

Cheriton School of Computer Science Professor Jimmy Lin has spearheaded the creation of a dedicated search engine for those who are engaged in the fight against COVID-19.

Friday, February 14, 2020

AI should not leave structured data behind!

photo of Ihab Ilyas

The following is an article written by Professor Ihab Ilyas, a faculty member of the Data Systems Group and the Thomson Reuters Research Chair in Data Cleaning from Theory to Practice

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