UBC Computer Science Professor Mark Schmidt Appointed Canada Research Chair in Machine Learning

UBC Computer Science Assistant Professor Mark Schmidt is the new Canada Research Chair in Machine Learning.  He is one of 18 newly-appointed Canada Research Chairs at UBC. 

The amount of data we collect is growing at unprecedented rates. We no longer talk about megabytes to gigabytes, but rather about terabytes to petabytes and beyond. It is impossible to manually analyze such data sets and this is leading to a surge of interest in the field of machine learning, which studies how we can use computers to automatically "learn" from these huge quantities of data to make predictions about the world and to help us make decisions. Machine learning is behind technologies like the recent major improvements in speech recognition, and has the potential to influence big data applications from physics to biology, and from human-computer interaction to education technology.

Dr. Schmidt is an expert in the area of machine learning and numerical optimization, and his influential work focuses on the challenges associated with learning complicated models from huge datasets. In some cases, Dr. Schmidt's work has lead to methods that are several times faster than previous approaches, and he is well-known for his computer software packages that let other researchers apply cutting-edge methods to their own problems.

Dr. Schmidt is using Canada Research Chair support to explore how to learn efficiently in new domains, such as social networks and exploration seismology, and how to maximally use new computing models, such as huge clusters of networked computers. By speeding up the core technologies underlying using larger datasets, this work has the potential to affect a wide variety of scientific and engineering disciplines that produce huge datasets, in both academia and industry.