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Applied AI

Leveraging the underlying science, operational research collaborates with industry to apply AI to specific problems and opportunities. We aim to develop lightweight, compact AI with minimal computing power and energy requirements, suitable for a host of stand-alone applications.

AI for Automotive & Manufacturing

The future of transportation and autonomous vehicles is no longer just a visionary dream. At the University of Waterloo, the Watonobus traverses the ring road loop on UW campus in a driver-less autonomous mode, sensing automatically the bus stops and passenger pick-ups and drop-offs. It is envisioned that in the not too distance future, these types of reliable and autonomous transportation options will be ubiquitous.

Manufacturing organizations are leading that charge with autonomous vehicles moving proficiently and working collaborative with employees throughout facilities in a wide variety of industries. But the opportunity is significantly larger, with the demand for next levels of AI for the optimization and automation of manufacturing processes to improve quality and overall efficiency.

AI for Climate & Social Good

Outside of improved business operations and profitability, the potential for using AI in climate applications is widespread including wildfire and disaster management, water applications related to stream flow, irrigation as a few examples. Further to this, the Social Good aspects for use of AI to help the aged, our youth and those with disabilities is enormous.

AI for Finance & Insurance

With the goal of managing financial risk while improving operational efficiency, many in the Banking and Insurance sector are leading the way with the implementation of Data Science and AI into their short, medium and long-term strategic planning, to ensure sustainability and competitiveness on a regional, national and international level.

Foundational AI

Foundational research allows us to identify – and subsequently overcome – shortcomings in existing artificial intelligence (AI) approaches. This not only strengthens the scientific base of the field but is also critical to further advancing real-world AI applications.

AI for Health

The potential for harvesting health data to provide new insights and understanding promises to yield potential breakthroughs in the prognosis and treatment of a wide range of health concerns from public health and the spread of disease to early warnings in ocular degeneration to name a few. More words needed here.

AI for Security

Cybersecurity is paramount to the future of society at large, as it is dovetailed with the increased implementation AI systems. Reliable cybersecurity is required across all industries with the field growing dynamically in leaps and bounds in our evolving digital landscape. Across all sectors, the demand for next generation innovative solutions combining AI and cybersecurity are required to deliver responsible, ethical and trustworthy solutions to humanity.

AI for Supply Chain

The challenges for every product-based organization are cost, quality and on-time delivery. Related to both internal and external supply chain challenges, the overall goal of implementing AI for Supply Chain is to bring dynamic real-time insights for capacity planning, enhance flow of quality goods for an organization, profitability while creating more rewarding and safer working conditions.