Ryerson Brings Education and Industry Together
Development and Innovation Learn more about why Ryerson University's Faculty of Engineering & Architectural Science is at the forefront of data analytics and machine learning.
Data Science Lab Professor and Director Dr. Ayşe Başar Bener explains why Ryerson is Canada's top comprehensive innovation university, with professional programs, research centres, and innovation zones that position it as a valuable partner to solve industry, government and community problems.
Mediaplanet: How is Ryerson at the forefront of applied learning when it comes to data analytics and machine learning?
Dr. Ayşe Başar Bener: In the data science research cluster, we work with post-graduate students to conduct research into building machine learning algorithms by analyzing data to build predictive models and achieve certain outcomes. The problems we work on differ depending on the industry. For finance, for example, we build models to detect change points and trade patterns. We’re also building a context aware intelligent algorithm for IBM’s Watson product to improve the relevancy of its recommendations—research that could apply to a wide variety of industries.
MP: How do these partnerships help Ryerson students?
ABB: Our students are able to gain experience and tackle real-world problems such as improving clinical outcomes in the emergency room, or predicting risk in insurance claims. They gain an understanding of industry challenges and how to build machine learning models that can immediately be used in industrial settings. They also come away with a valuable network of contacts.
MP: How do these relationships benefit your industry partners?
ABB: Simply put, we help organizations fill their talent pipelines while also providing solutions to business problems. We have a certificate program in data analytics, Big Data, and predictive analytics, and a master’s program in data science and analytics. Both of these programs graduate people who will go directly into industry as data analytics professionals, data scientists or chief data science officers. One of our recent graduates worked on our project with IBM Toronto Labs to use analytics to predict software defects. He now works at a company performing similar tasks. Our PhD students are able to develop novel algorithms and high dimensional data analysis techniques to improve well-known algorithms, and to complete the theoretical work that needs to be done before creating a commercial application.
MP: Who are some of the partners you’re currently working with?
ABB: We’re working with two different software development teams at IBM, as well as the IBM Watson Analytics group. We’re also working with data analytics and research teams at St. Michael’s Hospital, and partnering with the Toronto Stock Exchange to understand change points in the market. We also work with Toronto Police Services, Communication Research Centre Canada, Manulife and Mozilla.
MP: What’s the one thing you tell students and organizations considering Ryerson?
ABB: Ryerson has always been a leader in applied learning. We provide students with invaluable exposure to real-life problems, allowing them to see the tangible results of what they’re learning. Organizations can also benefit from our expertise in applied learning. We work with business units and data science teams to help them improve efficiencies in their day-to-day operations, give them tools to better understand their customers to boost their revenues, or to help them create new “data” products to maintain their competitive edge. Our students bring true value to our industry partners.