Friday, February 15, 2019

University Professor M. Tamer Özsu receives 2018 Lifetime Achievement Award in Computer Science

photo of University Professor M. Tamer Özsu

University Professor M. Tamer Özsu has received the 2018 Lifetime Achievement Award in Computer Science from CS-Can/Info-Can. Conferred annually since 2014, these prestigious national awards recognize faculty members in departments, schools and faculties of computer science who have made outstanding and sustained achievement in research, teaching and service. 

Wednesday, February 13, 2019

Hemant Surale receives prestigious 2019 Snap Research Fellowship

Hemant Surale in lab

PhD candidate Hemant Surale is one of 11 recipients globally and the only candidate from Canada to receive a prestigious 2019 Snap Research Fellowship. These fellowships were established to foster collaboration between Snap Research and exceptional doctoral students across the world.

Monday, February 11, 2019

Building the next generation of tech leaders in Africa

Nadayar Enegesi (BCS ’13) computer science alumnus and Andela co-founder, Iyinoluwa Aboyeji (BA ’12), legal studies alumnus and

Alumni startup Andela receives $180 million investment

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.

Friday, February 8, 2019

Making homes smart could become easier

photo of Ali Abedi, Tim Brecht, Omid Abari and Farzan Dehbashi

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.

Thursday, February 7, 2019

Maura Grossman named Director of Women in Computer Science

photo of Maura Grossman

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. 

Monday, February 4, 2019

Professor Bin Ma receives $463k grant from Genome Canada to improve precision medicine

Photo of Professor Bin Ma

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.” 

Friday, January 25, 2019

Ahmed Sabie, a third-year computer science student, places first in coding portion at fourth annual Code/Design to Win finals

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.

Tuesday, January 22, 2019

Letter to the Editor: TAR and Privilege Review

photo of Maura Grossman

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.

Thursday, January 17, 2019

Measuring AI's ability to learn is difficult

photo of Professor Shai Ben-David

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.