Back in 2016, on a sticky late-August day, a guy named Mark walked through the streets of Yaba, a historic neighbourhood in Lagos, Nigeria. He was keeping it low key. Just a few handlers and security guards sweating buckets in the heat as they all made the two-kilometre journey on foot.
Making your house “smart” could soon become cheaper and easier, thanks to new technology developed by researchers at the David R. Cheriton School of Computer Science.
Their recent study describes an approach that can be used to deploy, for the first time, battery-free sensors in a home using existing WiFi networks. Previous attempts to use battery-free sensors ran into some obstacles, making the efforts impractical. These hurdles include the need to modify existing WiFi access points, challenges with security protocols, and the need to use energy-hungry components.
Maura R. Grossman is a Research Professor and Director of Women in Computer Science at the David R. Cheriton School of Computer Science, as well as an eDiscovery attorney and consultant in Buffalo, New York.
A team of five students from the University of Waterloo has won the CBC Digital Products Award at CBC/Radio-Canada’s Hackathon 2019, the public broadcaster’s first-ever national bilingual hackathon held simultaneously at the CBC Broadcast Centre in Toronto and at Maison de Radio-Canada in Montreal.
Cheriton School of Computer Science Professor Bin Ma has received $462,998 in research support from Genome Canada for an ambitious three-year project titled “Software for peptide identification and quantification from large mass spectrometry data using data independent acquisition.”
The following article, titled “Waterloo students snag top prizes at code/design to win,” was written by Bill Bean and appeared originally in the January 19, 2019 issue of Communitech News.
The following article, titled “Letter to the Editor: TAR and Privilege Review,” originally appeared in the January 17, 2019 issue of the New York Law Journal.
We strenuously disagree with the notion that the use of technology-assisted review or TAR to assist with the privilege review in the Cohen case would have rendered it unfair or unconstitutional.
Organizations looking to benefit from the artificial intelligence (AI) revolution should be cautious about putting all their eggs in one basket, a study from the University of Waterloo has found.
The study, published in Nature Machine Intelligence, found that contrary to conventional wisdom, there can be no exact method for deciding whether a given problem may be successfully solved by machine learning tools.
Professor Shai Ben-David and his colleagues Pavel Hrubes, Shay Moran, Amir Shpilka and Amir Yehudayoff have shown that a simple machine learning problem — whether an algorithm can extract a pattern from limited data — is mathematically unsolvable because it is linked