Tuesday, November 9, 2021

AfriBERTa brings the power of natural language processing to African languages

photo of Kelechi Ogueji in the Davis Centre

Researchers at the Cheriton School of Computer Science have developed a data-efficient pretrained transformed-based neural language model to analyze 11 African languages. Their new neural network model, which they have dubbed AfriBERTa, is based on BERT — Bidirectional Encoder Representations from Transformers — a deep learning technique for natural language processing developed in 2018 by Google. 

Monday, November 8, 2021

Computer science PhD student and pro squash player Cameron Seth sparks entrepreneurship with SethSquash platform

photo of Cameron Seth playing squash

As a graduate student in the Cheriton School of Computer Science, Cameron Seth studies graph theory algorithms and complexity theory. As an athlete, he is among the top Canadian men’s squash players. He has been playing on the international professional tour since 2015, and during his undergrad, Cameron was a mainstay on the University of Waterloo varsity team.

Thursday, November 4, 2021

Company co-founded by Cheriton School of Computer Science alums attracts $37-million CAD financing round

photo of Griffin Keglevich, Ruslan Nikolaev and Rob Khazzam

A company founded by two University of Waterloo graduates is on track to become a giant in the Canadian business-to-business credit card market.

Float, which was co-founded by Cheriton School of Computer Science alums Griffin Keglevich and Ruslan Nikolaev, recently brought in a whopping $37 million CAD in new investments.

The company’s third co-founder and current CEO, Rob Khazzam, who joined Float in March 2021, brings a wealth of experience in business and finance, having previously worked for Uber and various venture capital advisory firms.

Thursday, October 28, 2021

Computer scientists developing method to identify disease biomarkers with high accuracy

photo of Fatema Tuz Zohora

Researchers at the Cheriton School of Computer Science are incorporating a deep learning network into a more accurate method to identify disease biomarkers. The new method achieves up to 98 per cent detection of peptide features in a dataset. That means scientists and medical practitioners have a greater chance of discovering possible diseases through tissue sample analysis.

Monday, October 25, 2021

Can we reach consensus on how AI will be used, regulated and interwoven into society?

photo of Research Professor Maura R. Grossman

Maura R. Grossman, JD, PhD, is a Research Professor in the Cheriton School of Computer Science, an Adjunct Professor at Osgoode Hall Law School, and an affiliate faculty member of the Vector Institute for Artificial Intelligence. She is also Principal at Maura Grossman Law, an eDiscovery law and consulting firm in Buffalo, New York.

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