Waterloo celebrates five Early Researcher Awards recipients

Ontario government ERA winners
Ontario government ERA winners
From developing artificial pancreatic devices to advancing research on the respiratory system and more, Waterloo researchers continue to lead breakthrough projects  

The Ontario government recently announced funding for five University of Waterloo faculty members to advance their research projects. The announcement was made as part of an investment into Ontario-based researchers whose projects will help to create jobs, technologies and accelerate economic growth. 

The five Waterloo researchers will receive funding through the Early Researcher Awards program - a program that gives research funds to new researchers working at publicly funded Ontario research institutions to build a research team.  

"We are immensely grateful to the Ontario government for their investment in the University of Waterloo’s researchers through the Early Researcher Awards," says Charmaine Dean, vice-president, Research and International. "The funded projects reflect Waterloo’s wide variety of cutting-edge research, from an examination of the impacts of COVID-19 on minority tourism social entrepreneurs to a new transdermal patch to track and treat diabetes without pain. Waterloo is advancing innovation in many impactful areas to develop new technologies and boost economic development." 

Each award from government is valued at $100,000, and is matched by an additional $50,000 from the researcher’s institution. These research projects that will no doubt have lasting positive impacts - learn more about the ground-breaking researchers and their projects below. 

Understanding the supports required by equity-deserving tourism social entrepreneurs in COVID-19 recovery and their implementation of the United Nations Sustainable Development Goals 

Equity-deserving groups have been under-represented in the entrepreneurial ecosystem s’in Ontatio and COVID-19 has exacerbated this. The proposed study uses a feminist intersectional and care lens employing case study and grounded theory methodologies focused on the Toronto-Waterloo Technology Corridor. The goal of the study is to improve understandings of the multiple intersectional barriers faced by equity-deserving technology tourism social entrepreneurs and appreciate their contributions to the United Nations SDGs. Findings will point at new directions for policy making, lifting and nurturing equity-deserving tourism social entrepreneurs and research to support an inclusive entrepreneurial ecosystem.

Longhouse Labs (LLabs) 

The Longhouse Labs (LLabs) is a research-creation hub aimed at facilitating long-term engagement with Indigenous artists, curators, conservators and researchers through the creation of yearly residencies (or Fellowships) within fine arts. Collaborative engagement opportunities between Fellows, Highly Qualified Personnel (HQP) and other stakeholders will be nurtured by the LLabs through research-creation and outreach activities. The LLabs is designed to accommodate broad and intersecting studio practices by offering: a cluster of studios, new media supports, archival infrastructure, collaborative-research spaces and land-based research areas and materials. Through a model of reciprocity, the LLabs meaningfully fosters innovative, interdisciplinary research opportunities that explicitly promote Indigenous leadership in studio arts practices as part of core learning experiences in the fine arts, and represents concrete action towards Indigenous inclusion in response to the Truth and Reconciliation Commission’s (TRC’s) Calls to Action.  

A new transdermal patch to continuously and without pain track and treat diabetes 

Diabetes, if left unchecked, can cause serious illnesses leading to healthcare burden in Ontario. Patients with diabetes often require injecting insulin to balance their blood glucose level. Artificial pancreas devices (APDs), combining a continuous glucose monitor with an insulin pump, have revolutionized diabetes care as they enable insulin delivery automatically in response to real-time glucose measurements. However, there is a high risk of giving excess insulin due to the lack of insulin kinetic measurements in the APDs causing a low blood glucose condition which can lead to coma and even death. Poudineh’s research will develop a new, low-cost APD system which is smaller (approximately seven centimetres) and capable of smart insulin sensing and delivery. This system can be easily applied by patients, without pain. 

Understanding the impact of sex-differences in the pulmonary system on exercise 

Chronic illness is a major financial and societal burden to Ontario, estimated at more than 55 per cent of the province’s total health care costs. Exercise can prevent and treat most chronic illness and substantially reduce this burden by approximately $3 billion per year with minimal cost and risk. The respiratory system is the first and last line of defense for maintaining adequate oxygen levels in the blood during exercise and is fundamental to the basic exercise response. Dominelli’s team seeks to further understand how sex-differences in the respiratory system impact the response to exercise to address the long-standing bias in exercise physiology where females are underrepresented in research, despite growing evidence of known differences that can impact exercise training and rehabilitation. This research will use advanced experimental techniques and technologies, utilizing participants from both sexes and across the lifespan, to provide detailed insights into how the respiratory system responds and impacts exercise tolerance.  

Pushing-forward deep generative models 

Generative models form an indispensable part of artificial intelligence, as they learn to generate new data that is similar to an existing dataset, with the overarching thesis that if we can automatically generate data then we must have gained significant knowledge and are ready to generalize. However, our understanding of the pros, cons and fundamental limitations of different generative models, as well as their connections to existing and more classical approaches, is still very limited. Yu’s research project will fill this gap by thoroughly investigating the central role of push-forward maps in generative modeling, as well as their estimation, optimization and inference This research wil enable the development of more efficient training algorithms that take inherent data structure and domain prior knowledge into account and build a distributed system for training lightweight generative models on low-cost edge devices, explicitly accounting for model robustness and data privacy.  
Darren McAlmont