Data Sciences Institute

DSI welcomes Women’s College Hospital as a partner

The Data Sciences Institute (DSI) is excited to announce a new partnership with Women’s College Hospital (WCH).  For more than 100 years WCH has been developing revolutionary advances in healthcare. Today, WCH is a world leader in health equity and Canada’s leading academic ambulatory hospital focused on delivering innovative solutions that address our most pressing issues related to population health, patient experience and health system costs.

“Women’s College Hospital (WCH) is reimaging and redesigning healthcare to enhance access, address inequities, and innovate more readily. To do that, we are leveraging data insights to identify areas for improvement, test new models of care and ultimately improve care for everyone. As a research leader in the field of data science, this collaboration with DSI will enable our teams to further their work, pursue new opportunities, and expand our partnership network,” said Dr. Rulan Parekh, vice president of Academics at Women’s College Hospital.

DSI collaborates with organizations eager to support world-class researchers, educators, and trainees advancing data sciences. We facilitate inclusive research connections, supporting foundational research in data science, as well as supporting the training of a diverse group of highly qualified personnel for their success in interdisciplinary environments. As one of our external funding partners, WCH researchers can apply for research grants, training and networking opportunities at the DSI.   

“We are delighted to announce this partnership with WCH. Our goal is to create a hub to elevate data science research, training, and partnerships. By connecting data science researchers, data and computational platforms, and external partners, the DSI advances research and nurtures the next generation of data- and computationally focused researchers. We are very excited to have WCH researchers join the DSI community.” - Lisa Strug, Director, Data Sciences Institute

DSI launches call for new ideas that push the boundaries of data science

Data science is an ever-evolving field. It continues to change, as new innovations come to light, and data scientists continue to revolutionize the way we use, analyze, collect and store data.  

Learn more about how you can apply.

Deadline LOI: March 3, 2023

Deadline full proposal: May 26, 2023

So, what is the next big thing for data science? 

The Data Sciences Institute (DSI) is launching a new Emergent Data Sciences Program competition designed to fund researchers and advance cross-disciplinary data science in areas where the University of Toronto is already a leader or has the capacity to become one. The DSI seeks to promote and expand the awareness and role of data science in all research activities across UofT. This call is intended to attract and develop new communities that want to enhance their activities using data science. 

Emergent Data Sciences Programs are a DSI core activity that helps fulfil its mission of bringing people together for collaborative generation and application of new ideas that support emergent areas in the data sciences. 

“At the DSI, we are proud to be a part of the University of Toronto, one of the world’s leading universities. I have no doubt that we will see many proposals that attempt to push the boundary of what has been done before from across UofT, as well as explore new multi-disciplinary applications of data science. We hope these will establish new fields and techniques that are so often the preludes to future scientific, technological and societal breakthroughs,” says David Lie, DSI Associate Director, Thematic Programming and Data Access.

When asked about what he thinks the next big thing in data science is Dr. Lie says, “The collection, application, and curation of large datasets focused on the public has been largely spearheaded by private entities trying to improve their enterprises and businesses. However, the Covid-19 pandemic demonstrated that there are a host of socially beneficial uses of that data. This is just the tip of the iceberg. I believe the next stage of data science will be to devise new techniques, and governance policies, that will enable data collected by private and public organizations to be shared and applied in other, important socially beneficial uses. To do this, we must overcome significant challenges, such as how we can share large data sets in privacy-preserving ways, and how we can identify and mitigate security risks that might arise. But this is just one example of many.”

Emergent Data Sciences Program proposals should include a broad span of activities that lead to the development of innovative data science methodologies, deep connections with computation and applied disciplines, new training programs, collaboration, knowledge mobilization, and impact. Ideal program proposals should establish or elevate local cross-disciplinary activity that advances the data sciences by pursuing the next big-but-yet-unknown data-driven field or computational or analytic breakthrough.  

Building environmental data sets to illustrate climate change in Northern Canada

DSI Catalyst Grants, supporting collaborative research teams for impact

Arctic regions experience climate change at a significantly faster rate than the rest of the planet. Residents in Northern Canada, and other Arctic regions, have long perceived anomalies in weather patterns, changes in long-standing sea ice patterns, and ecosystem stress. But these changes have been difficult to document, making it challenging to understand how they will ultimately impact human health and food security.  

The Data Sciences Institute (DSI) is funding cross-disciplinary research teams focused on using the data sciences to solve complex and pressing problems. Yuhong He (Geography, Geomatics & Environment, UTM) and Kent Moore (Chemical & Physical Science, UTM), one of the multidisciplinary collaborative research teams to receive a DSI Catalyst Grant, are using environmental data to help gain a more complete understanding of the changes happening in Northern Canada.  

“Cross-disciplinary data science research has the potential to solve some of the most pressing challenges we face today. Professors He and Moore’s research is just one example of many. We are beginning to see the impact of DSI Grants and the capacity of bringing collaborative research teams together. We are excited to see how Catalyst Grant recipients continue to catalyze the transformative nature of the data sciences,” says Gary Bader, DSI Associate Director, Research and Software.

The power of environmental data science

Professor Moore focuses on the cryosphere. The cryosphere is made up of all the frozen places on our planet like glaciers, continental ice sheets, permafrost, snow and ice. He uses theoretical, computational, and observational techniques to gain insights into the dynamics of the climate system. This helps place observed changes to our climate into a long-term context. 

Professor He’s research centers on the biosphere. She integrates multi-source remote sensing big data into ecological research for a better understanding of the drivers and mechanisms shaping these changes in vegetative ecosystems. Her research helps improve conservation efforts. 

Together the team uses Earth observation data and machine learning to reveal patterns and trends in land surface changes and their possible impacts on people. These results provide a crucial basis to develop long-term strategies to help cope with the climate crisis and its resulting environmental, societal, and economic impacts.   

The funding support from DSI increases the team’s capacity across a range of disciplines and helps them conduct an analysis of the environmental changes impacting northern Canada by developing open-access geospatial datasets. The funding also supports reproducibility and the establishment of an Earth observation data management system for sharing and using these datasets. Reproducibility is a DSI Thematic Program that strives for the development of widely adoptable methodology, processes, and infrastructure to share data and code locally and in privacy-compliant ways. 

Helping northern communities access reliable environmental data

“Pressing global issues like climate change require integrated, interdisciplinary approaches to successfully address research questions involving complex environmental systems. Both Professor Moore and I have extensive experience using Earth observation data and machine learning approaches, and our research on the cryosphere and biosphere make us an ideal team to establish a complete Earth observation data management system for northern Canada,” says Professor He.

For many northern communities, access to reliable data that illustrates the impact of climate change on regional ecosystems is difficult to access. An aggregate data set does not exist in a usable or scalable way. Local and regional approaches to environmental and climate action, like those taken by Nunavut’s Qaujigiartiit Health Research Centre, require access to longitudinal data to make informed decisions about the health of residents. The establishment of this Earth observation data management system will enable a network of researchers to upload, share, and download spatial data spanning a nearly 50-year period.    

“This research will not only advance and redefine our understanding of climate and ecosystems in this region but also provide potential users with direct knowledge and insights to develop local and regional adaptation strategies,” says Professor He.

Data science to make our society better

How do we get people to understand how data influences their lives?

Data science has infiltrated our everyday lives and, although a powerful tool, with it come cases of bias, injustice, and discrimination. Consider the emerging discourse around the metaverse, within which people only exist as data. These data provide opportunities for research and innovation, but also commodification and surveillance. 

So how do we conduct data science responsibly?

That’s exactly what the new DSI@UTM initiative is tackling. The DSI at the University of Toronto Mississauga is leading a tri-campus initiative to encourage research activity in Responsible Data Science that includes community-building, workshops and seed funding for research.

Data science will continue to restructure aspects of our world and it is important to maintain a commitment to questions of power, inequity, responsibility, surveillance, justice, and harm. Especially, to ensure that collecting, manipulating, storing, visualizing, learning from, and extracting useful information from data is done in a reproducible, fair, and ethical way.

Why is UTM the right place for this initiative?

UTM has a cluster of faculty working across questions of responsible data science. One example is the Institute of Communication, Culture, Information and Technology (ICCIT), which looks at technology, media, and society and considers how algorithms affect the world. The campus is also comprised of  researchers working on sustainability, management, and geography along with  initiatives focused on giving back to the Mississauga community, including working with Indigenous community leaders. 

During an interview about this initiative, Associate Director of the DSI@UTM, Professor Bree McEwan, highlighted the revised UTM Strategic Framework. The Framework expresses core priorities and commitments that will strengthen consensus, inspire action, and guide investment. It includes priorities such as embracing place and encouraging collaboration.

“Responsible data science is about how we do data science, not just for the purpose of doing data science, but doing data science in a way that is making our society, our environment, etc. better for everyone. Therefore, the idea of responsible data science fits hand in glove with the other pieces of the Framework at UTM. How do we get lots of people to understand how data influences their lives, the idea of responsible data science? At UTM, we already have some strengths in how what we do here at the University influences the community around us,” says McEwan.

“The University of Toronto Mississauga is brimming with world-class researchers, focused on changing the world. UTM is a great place for this initiative, and we are thrilled to be building this within the DSI, as responsible data science needs to be a key part of both our research at UTM and our daily lives,” says Elspeth Brown, Associate Vice-Principal Research (AVPR) in the Office of the Vice-Principal, Research (OVPR). 

Events to look out for

A big focus of this initiative is bringing researchers working with data science at the UTM campus, and beyond, together. On December 7, DSI@UTM will be hosting its first Data Digest, Data & Sustainability. These networking events feature UTM data science researchers and provide attendees with the opportunity to engage in Responsible Data Science. Each month will feature a selection of short interdisciplinary research-based talks on a topic and explore challenges and opportunities related to data science. 

In February 2023, DSI@UTM will be hosting a Data in the Metaverse workshop. This event seeks to imagine future possibilities, challenges, and implications of data creation, collection, analysis, and deployment in the metaverse. Current discussions of the metaverse and the increase in VR adoption make this an opportune time to consider how data can, is, and could be employed in virtual reality and immersive environments.

Critical Investigation of Data Science Grant

The DSI@UTM Critical Investigation of Data Science (CIDS) grant is designed to provide seed funding for scholars. Projects can vary in scope from the analysis of specific data science projects and approaches to the articulation of potential harms in data science from a broader perspective.

“It’s about putting our money where our mouth is, in that we should be inviting critique of the data sciences in order to improve the data sciences. These grants will allow people to have some support for exactly those kinds of projects. Building in this critical angle, this self-reflection, into the data sciences is also important to make sure that we are doing data science responsibly,” says McEwan.

Gift from Schmidt Futures to spark a revolution in AI-based STEM research at the University of Toronto

The Data Sciences Institute (DSI) is excited to co-lead the prestigious Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship a program of Schmidt Futures.  

With the goal of accelerating scientific research through the application of artificial intelligence, Schmidt Futures is investing $148-million in nine global universities, including the University of Toronto.

Apply to become an Eric and Wendy Schmidt AI in Science Postdoctoral Fellow.

The deadline is November 21, 2022.

The announcement launches the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a program of Schmidt Futures. A large-scale initiative supporting the work of early-career scholars in engineering and the natural sciences, such as mathematics, chemistry or physics, the program fosters their uptake of vital tools in artificial intelligence.

Artificial intelligence is not just a field in its own right but also an important tool for research. It can find patterns to enable research that solves important challenges—across fields from climate change to human health and beyond—more quickly and more efficiently. To accelerate the adoption of AI into scientific methodologies, the Schmidt AI in Science Postdocs initiative aims to spark a significant increase globally in the number of scientists working with cutting-edge AI tools.

A wide-ranging vision for solving global challenges

Schmidt Futures is a philanthropic initiative, founded by Eric and Wendy Schmidt, that brings talented people together in networks to prove out their ideas and solve hard problems in science and society.

The CEO of Google from 2001 to 2011, Eric Schmidt has hands-on experience with the transformative power of finding and supporting innovative minds—at scale. Wendy Schmidt, a journalist and a competitive sailor, has created multiple non-profits in the areas of global sustainability and human rights. With Schmidt Futures, their focus is on building networks of visionary minds with the talent to solve society’s problems.

The University of Toronto is Canada’s leading research university and the home of seminal work in artificial intelligence, from deep learning and neural networks to the interfaces between AI and the natural sciences.

“As the home of deep learning, the University of Toronto is proud to partner with Schmidt Futures on this forward-looking program, which will accelerate humanity’s ability to meet some of the most important challenges of our time,” said Meric Gertler, president of U of T. “The Schmidt AI in Science Postdocs program provides tremendous opportunities for the emerging generation of STEM researchers. On behalf of the U of T community, I would like to thank Schmidt Futures for their vision and generosity.”

The University of Toronto is the only Canadian university chosen for the program. Its highly diverse community—its existing postdoctoral fellows come from 89 countries—and global links make it an ideal centre to support the Schmidt AI in Science Postdocs global network.

“The Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a program of Schmidt Futures, will create an immediate acceleration of AI applications across several disciplines. We are proud to partner with these exceptional universities, especially the University of Toronto, on this important initiative,” said Stu Feldman, chief scientist at Schmidt Futures. “The Fellowship will provide these postdoctoral fellows with the advanced tools to increase the scope and speed of their research while discovering new and innovative use cases for AI within their field. U of T’s thoughtfully crafted program design, strong base of alumni in the scientific world, high volume of leading-edge scientific research, and deep history of important AI research give us full confidence in an impactful outcome.”

Creating a cohort of AI-fluent researchers

The Schmidt AI in Science Postdocs program will support nearly 300 postdoctoral fellows each year for six years. U of T hosts 10 in the first year of the program and 20 annually thereafter. The support includes networking and research collaborations between participating universities; a robust series of workshops, conferences and lectures; and training in how to apply AI techniques.

The fellows will not only expand the scope of their own research but will also establish their careers as AI-fluent scientists, ready to expand new research methodologies across a range of fields through their future work.

At U of T, the Schmidt AI in Science Postdocs becomes one of the university’s most prestigious postdoctoral programs. Working closely with the Vector Institute for Artificial Intelligence, two senior faculty members lead the initiative. Alán Aspuru-Guzik is the director of U of T’s Acceleration Consortium, a global network of researchers, industry and government that is leading a convergence of materials science with AI and robotics. Lisa Strug is the director of U of T’s Data Sciences Institute, one of the world’s largest clusters of scientists working on innovative approaches to data that drive actionable research insights.

“The Data Sciences Institute (DSI) is excited to co-lead the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship. This large-scale initiative supports postdoctoral researchers in engineering and the natural sciences by giving them vital tools in artificial intelligence. The DSI is thrilled to have the opportunity to support this new prestigious global program and help early career researchers innovate in their fields,” says Lisa Strug, director of the DSI and Associate Director of The Centre for Applied Genomics at The Hospital for Sick Children.

Canada Research Chair in Genome Data Science, Lisa Strug is a statistical geneticist in the Faculty of Arts & Science who develops novel approaches to identifying the genetic contributors to complex human disease. She is cross-appointed to the Dalla Lana School of Public Health and the Hospital for Sick Children and is also the director of the Canadian Statistical Sciences Institute, Ontario Region.

As a CIFAR AI Chair at the Vector Institute for Artificial Intelligence and the Canada 150 Research Chair in Theoretical and Quantum Chemistry, Aspuru-Guzik works to accelerate the discovery of new molecules and materials needed for a sustainable future, using novel, disruptive approaches. He is also a Google Industrial Research Chair in Quantum Computing and is the founder of two startups.

Canada Research Chair in Genome Data Science, Lisa Strug is a statistical geneticist in the Faculty of Arts & Science who develops novel approaches to identifying the genetic contributors to complex human disease. She is cross-appointed to the Dalla Lana School of Public Health and the Hospital for Sick Children and is also the director of the Canadian Statistical Sciences Institute, Ontario Region.

As a CIFAR AI Chair at the Vector Institute for Artificial Intelligence and the Canada 150 Research Chair in Theoretical and Quantum Chemistry, Aspuru-Guzik works to accelerate the discovery of new molecules and materials needed for a sustainable future, using novel, disruptive approaches. He is also a Google Industrial Research Chair in Quantum Computing and is the founder of two startups.

“Thank you, Schmidt Futures, for this generous vote of confidence in U of T programming and in the exceptional talents who thrive in our postdoctoral programs,” said Leah Cowen, U of T’s vice-president for research, innovation, and strategic initiatives. “The prestigious Schmidt AI in Science Postdoc program will help catalyze novel solutions to tough challenges. It is the kind of thoughtful support that powers real innovation.”