Cheriton School of Computer Science Professor Gautam Kamath has been named a Canada CIFAR AI Chair and a Vector Institute Faculty Member in recognition of his contributions to differential privacy, machine learning and statistics. He is among eight outstanding researchers in the latest cohort of Canada CIFAR AI Chairs to receive this prestigious national recognition.
“Congratulations to Gautam on becoming a faculty member of the Vector Institute and on being named a Canada CIFAR AI Chair,” said Raouf Boutaba, Professor and Director of the Cheriton School of Computer Science. “Gautam’s research focuses on developing solutions for trustworthy and reliable machine learning and statistics. The fundamental work he and his students conduct is critically important as it allows useful insights to be drawn from data while preserving privacy of sensitive personal information.”
These recent appointments bring the number of Canada CIFAR AI Chairs to 126, continuing to grow Canada’s robust artificial intelligence research ecosystem and advancing Canada’s global leadership in artificial intelligence.
Learn more about about CIFAR, and the Pan‐Canadian Artificial Intelligence Strategy at CIFAR, at Waterloo News.
About Professor Kamath’s research
Statistics and machine learning are being used ever more commonly in a variety of disciplines from the physical and social sciences to the humanities, at scales from small groups to entire populations, across sectors as diverse as government, finance and health. The data on which statistics and machine learning techniques are applied often is both sensitive and confidential and, as such, can attract the attention of malicious individuals and groups.
The demands of modern data analysis — most notably guaranteeing data privacy — quite simply were not envisioned when classical statistical methods were developed. In fact, if statistical techniques are applied without consideration for privacy, information can be leaked about the data, and in extreme cases even actual data points themselves upon which the statistical estimations are based.
Professor Kamath’s research revitalizes the toolkits needed in the modern data era, addressing fundamental problems in the realms of robustness and data privacy, by developing guarantees for trustworthy and reliable machine learning and statistics. He and his students have made seminal and significant contributions to both areas — in the theoretical foundations of data privacy as well as in its practical applications — initiating broad new research fields, and contributing core components to deployments that touch the sensitive personal information of hundreds of millions of individuals.
Canada CIFAR AI Chairs at the Cheriton School of Computer Science
Professor Kamath is the sixth faculty member at the Cheriton School of Computer Science to be named a Canada CIFAR AI Chair, following Professors Shai Ben-David, Wenhu Chen, Xi He, Pascal Poupart, and Yaoliang Yu.