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During his inaugural lecture at the University of Lille in 1854, the French microbiologist and chemist Louis Pasteur said, “In the fields of observation chance favours only the prepared mind.”

Pasteur’s reflection is as true today as it was more than a century and a half ago. Those who observe the world keenly with minds that have been primed by experience and education will see novel ideas to pursue, original opportunities to explore.

Former computer science student Vitalik Buterin, founder of the cryptocurrency Ethereum, has been named in the recent Forbes ‘30 under 30 hall of fame.’

photo of Vitalik Buterin
On this tenth anniversary of the Forbes 30 under 30 lists, the publication included a best of the best from the past ten years, noting those who had been named the most times or consistently in the lists.

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. 

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.

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.

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.

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.