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Data science and AI have enormous potential to empower communities, address important societal questions and drive positive change. The Data Sciences Institute’s Summer Undergraduate Data Science (SUDS) Opportunities Program has supported a number of projects focused on advancing the social good. Through partnerships and faculty-led research projects pursuing topics such as the impact of speed enforcement on road safety disparities, the effect of built environment factors on breast cancer risk, and the economic benefits of green cities, students gain hands-on experience while participating in training and professional development.

Now, thanks to the support of Birch Hill Equity Partners Data Science, DSI is building on this momentum by launching the SUDS Data Science & AI for Social Good stream. This new stream will expand opportunities for undergraduate students to work with U of T’s leading data scientists and AI researchers on projects addressing important societal questions.

The Data Science and AI for Social Good stream will support four research projects in 2027. A call for faculty members and principal investigators who may have a position available will open in September.

Birch Hill Data Science is committed to advancing socially impactful data science and training the next generation of data science talent. With Birch Hill Data Science’s support, the range of projects that apply data science and AI tools and practices to further social good will continue to expand. The new stream aims to create new opportunities for the work of non-profits and agencies and for the communities they serve, for example, by supporting the use of data science and AI in health research to improve treatment and lives.

“We see tremendous potential in bringing together academic expertise, emerging talent, and organizations working to address societal challenges,” says Birch Hill Data Science Managing Director Gary Glasser. “Supporting this initiative is an opportunity to help unlock the power of data science and AI for real-world impact.”

SUDS enables undergraduate students who are interested in exploring data science and AI as a career path to engage in hands-on research led by U of T faculty and scientists from external funding partners, including SickKids, CAMH, and the Ontario Institute for Cancer Research. Now in its fifth summer, SUDS has supported more than two hundred research projects, each led by a faculty supervisor, enabling more than three hundred undergraduate students to gain research experience in data science and AI.

“One of the most exciting parts of supervising a SUDS project is seeing undergraduate students contribute meaningfully to a complex challenge that impacts the world around them. It is wonderful to see this expand with even more opportunities for students to bring their strong data science skills while learning about ways that their research careers can create positive change,” says Professor Brice Batomen Kuimi, Dalla Lana School of Public Health, supervisor for a SUDS project investigating road safety disparities.

Lisa Strug, Director of the Data Sciences Institute, highlights that Birch Hill Data Science’s generous support is an important development in DSI’s work to accelerate the impact of data sciences. “Data science and AI have enormous potential to address societal challenges, but many organizations lack the capacity to fully leverage these tools. We are very pleased for the generous support of Birch Hill Data Science to launch the Data Science and AI for Social Good stream and create opportunities for our students to apply their expertise working to make a meaningful difference in their communities.”

Advanced AI models are increasingly becoming a critical research resource, similar to access to data, computing infrastructure, and specialized software. Access to these models, however, can be a barrier for researchers and trainees without the resources to experiment with and deploy frontier AI models in their work.

A gift from AI company Anthropic will provide $1 million in Claude API credits to support research and education at the Data Sciences Institute at the University of Toronto. These usage credits will grant access to Claude’s Application Programming Interface (API), which enables interaction with Claude models. The initiative will equip researchers with access to cutting-edge AI tools that can support discovery, analysis, software development, and innovation across disciplines. 

As a hub for research, training, and industry collaboration, bringing together faculty, students, and partners, DSI advances data-driven discovery through interdisciplinary research, training, and partnerships that translate data science into real-world impact. DSI will launch a competitive process for the Claude API credits, leveraging existing grant experience and infrastructure. DSI’s programs, such as the Data Access Grant Program and Research Software Development Support Program, provide a proven model for competitions, with scientific review panels ensuring funding and in-kind support is awarded to high quality, and impactful projects.

Enabling access to emerging data science and AI capabilities across the research community is an important part of DSI’s mission. Since 2021, DSI has awarded $19 million in research and trainee funding to more than 500 researchers from across all three U of T campuses and DSI external funding research institutes. DSI member researchers have leveraged these funds to secure over $126 million in external grants enabling researchers to make significant contributions to their fields.

“At DSI we are very pleased to be taking on this role in stewarding and distributing the credits. Opportunities like these to enable applications of AI tools and methodologies are an important part of how we drive research excellence and impact,” says Professor Gary Bader, Associate Director, Research & Software, Data Sciences Institute. “Building on the university’s strong history of leadership in artificial intelligence, the University of Toronto Data Sciences Institute will launch a competitive process to access Claude API credits, with a scientific review panel ensuring they are awarded to safe, high quality and impactful research.”

“The University of Toronto continued advancing neural network research when most of the field had moved on, helping prove it could work at scale. That long-term commitment to getting AI right is something Anthropic is built on, and we’re glad to be supporting future innovative U of T research with Claude,” says Brian Peters, Head of North America Government Affairs at Anthropic.

The initiative strengthens U of T’s position as a global leader in AI and interdisciplinary research. The university ranks among global leaders for the study of data science and artificial intelligence, ranking thirteenth in the 2026 QS World University Rankings.

“U of T has a strong history of leadership in artificial intelligence. This new initiative with the Data Sciences Institute, will provide access to cutting-edge AI tools to researchers and will open new possibilities for discovery, analysis, and innovation across the university,” highlights Leah Cowen, Vice-President, Research and Innovation, and Strategic Initiatives, University of Toronto

Full details of the call for applications for this new initiative are now available. The competition will run from July 20 to September 25, 2026.

This summer, machine learning models created by participants in a series of DSI-supported bootcamps will be used to identify drug-like hit molecules from commercial libraries – and DSI funds will allow the team to purchase the predicted molecules and test them experimentally in the lab.

“A hit molecule is a first instance of a bioactive molecule,” explains Prof. Matthieu Schapira (Department of Pharmacology and Toxicology, Temerty Faculty of Medicine, University of Toronto; PI, Structural Genomics Consortium), one of the co-leads of Galvanizing Data Science Applications in Early Stage Drug Discovery. “That’s one of many areas where AI can have an impact in drug discovery. Here, it’s really focused on finding chemical hits, but the whole drug discovery pipeline is going to be impacted by AI. This particular program is focused on one of the earliest steps.”

To date, almost 200 people have completed the CrossTALK: Cross-Training in AI and Laboratory Knowledge for Drug Discovery bootcamps on data science for hit-finding, or designing drug-like molecules for a given protein target. The training enables trainees from biological sciences to learn about machine learning and its data needs, while trainees from the computer sciences experience the nuances of chemical and biological data. The hope, says Prof. Schapira, is to foster a new generation of scientists who understand both languages and thought processes.

AI’s impact on drug discovery is just one of the emergent areas of data science supported by the Data Sciences Institute. These interdisciplinary areas advance the data sciences by pursuing the next big-but-yet-unknown data-driven field or computational or analytic breakthrough in interdisciplinary areas where the University of Toronto excels. The DSI’s Emergent Data Sciences Program funds activities and provides administrative support to coordinate events, communications, and programming, as well as grant-writing support.

  

“Bringing people together for collaborative generation and application of new ideas in the data sciences is a core part of DSI’s mission,” says Prof. Meredith Franklin, DSI Associate Director, Joint Initiatives. “From law, public policy and economics, to biophysics, aerospace studies, pharmacology and beyond, the Emergent Data Sciences Program has touched on an inspiring range of disciplines – and we hope to see that breadth continue to grow. We’ve seen how these collaborations between methodologists and other researchers set the stage for essential dialogue and future impacts including grant proposals and expanded programs.”

Currently, there are three active Emergent Data Science Programs: Bridging the Gap: From Computational Physics, to Physics-informed Machine Learning, to Data-driven Scientific Discovery, Advancing Aging and Neurodegeneration Research through Data Science, and Galvanizing Data Science Applications in Early Stage Drug Discovery.

Bridging the Gap: From Computational Physics, to Physics-informed Machine Learning, to Data-driven Scientific Discovery is the newest of the three programs. It brings together experts in numerical simulation and data science to explore the intersections and bridge the gap between physics-based models based on first principles in sciences and engineering, and data-driven models based on machine learning techniques.

Since March 2026, three mini symposia and a two-day conference have brought together over 200 participants from across U of T and internationally, enabling collaboration and driving research towards truly predictive simulation capabilities that guide scientists and engineers making crucial decisions with high societal impact, ranging from sustainable design to medicine to astrophysics.

Advancing Aging and Neurodegeneration Research through Data Science addresses challenges in accelerating the impact of AI in clinical settings through engagement with diverse audiences, including talks by renowned researchers in brain and body imaging and a workshop on Advanced Data Science Approaches to Studying the Aging Brain. These collaborative opportunities bring together data scientists, clinicians, and educators, to discuss the development of new areas of research that can ultimately benefit the treatment, care, and healthcare service delivery for older adults.

As for the Galvanizing Data Science Applications in Early Stage Drug Discovery program, Prof. Schapira highlights that what the program has achieved with DSI’s support is just the beginning. “Every time I talk about this with professors in other Canadian universities, they are super excited to say they want to be a part of the next phase. And so I’m confident that we could put together more Canadian programs to do this. It needs to be embedded within departmental activities to be sustainable and with long-term funding. And I’m pretty confident we’re going to get there.”

Applications are now open for the Emergent Data Sciences Program. Letters of Intent are due November 20, 2026.

This week, Canada’s Minister of Artificial Intelligence and Digital Innovation, Evan Solomon, announced the launch of Vital — a national initiative that will connect health data across Canada for research and innovation — in one of the largest investments in Canadian history for health data innovation.

Data science and data science talent play a key role in productive, trustworthy, socially valuable AI. As part of the newly announced national initiative, the Data Sciences Institute will lead the development of statistical methods and software tools to enable advanced analytics in federated environments for healthcare.

Total investments in the Vital platform include a $30 million initial investment from Innovation, Science, and Economic Development Canada; a Canada Foundation for Innovation award for a total budget of $68 million (including federal, provincial and institutional contributions); and financial contributions from provinces, bringing foundational funding to over $100 million. An additional $100 million was also announced in the Federal AI Strategy in June to expand Vital across Canada, bringing the project’s full funding to over $210 million.

“Better health data can mean better health care” says Solomon, who announced the funding at an event at St. Michael’s Hospital on June 23. “Every day, our hospitals generate information that could help researchers discover new treatments, improve services and build the next generation of Canadian health innovation. VITAL will help unlock that potential in a secure, privacy-preserving way. By investing in VITAL, we are building a sovereign health data ecosystem, governed in Canada and guided by Canadian values, so that data and AI can deliver better care for Canadians.”

Vital – based at St. Michael’s Hospital, a site of Unity Health Toronto – will deliver near real-time health data from hospitals in provinces across Canada, beginning with 160 hospitals in Alberta, Ontario and Quebec. Its data is particularly valuable for AI development and evaluation because of Canada’s diverse population, high-quality healthcare and inclusive single-payer system. Vital will connect data across provinces using a federated approach that allows data to stay within the authority of each participating province, with Vital providing the essential connections so that data can be analyzed together. This means researchers and innovators can access data across Canada, making their discoveries more useful to more people.

As part of this national initiative, the Data Sciences Institute research associates and research software developers will work with researchers and Vital and provincial platform teams to build up facility and methodology for federated statistical analysis as well as software to access Vital data, providing these tailored tools and methods to users. The DSI research associates will work one-on-one with researchers and will also develop tools that provide access to useful datasets and advanced methodological techniques. The suite of methods for federated analysis of electronic health record (EHR) data, for example, will enable users to analyze data across distributed provincial environments while respecting provinces’ respective privacy regulations.

AI tools that develop outcomes for research from medical imaging and physician notes and cutting-edge federated computational tools for analysis across provinces are just some of the exciting examples of this work. Vital will strengthen Canada’s competitiveness by enabling faster, more efficient clinical trials; accelerating commercialization of health innovations; attracting private sector and global AI investment; and providing a national platform for Canadian companies to scale, while reducing inefficiencies across a multi-billion-dollar health system.

“Human expertise in the data sciences and data quality is essential to Canada’s AI performance. DSI is a perfect hub for building the statistical methodology for federated statistical analysis to expand Vital’s user base and research applications. We are very proud to play this role in developing the system as an integral feature of Canadian cutting-edge research,” says Lisa Strug, Director of the Data Sciences Institute.

DSI research associates will liaise between Vital and researchers in an approach modeled on the existing DSI Research Software Development Office, which supports DSI faculty and scientists across fields by providing access to highly skilled software developers who refine or enhance existing software, build new tools, and ensure reproducible research processes.

DSI has supported Vital since 2023. As part of GEMINI, one of the foundational programs underpinning Vital, the DSI team developed a user-friendly web portal to seamlessly and securely distribute healthcare quality reports for the General Medicine Quality Improvement Network (GeMQIN), a program of Ontario Health. The DSI software support provided web development capacity and skillset to create a portal allows the GEMINI team to easily manage their users, upload reports, and access administrative controls, creating a more efficient and user-friendly experience.

This new collaboration will leverage and expand this office to include research associates with the expertise to reduce obstacles to preparing Vital’s data for research-ready use cases. Through the development, implementation and management of statistical methods, state-of-the-art approaches and implementation for Vital-derived variables, and AI-ready data and tools, DSI will enable discoveries that further cement Canada as a leading research hub.

Photo provided by Unity Health Toronto.
(L-R) Caroline Lidstone-Jones, CEO of the Indigenous Primary Health Care Council; Amol Verma, physician and scientist in General Internal Medicine at St. Michael’s Hospital and Temerty Professor of AI Research and Education in Medicine at the University of Toronto; Danielle Martin, Member of Parliament for University—Rosedale; Altaf Stationwala, president and CEO of Unity Health; Helena Jaczek, Member of Parliament for Markham—Stouffville, Ontario; Maggie Chi, Parliamentary Secretary to the Minister of Health; The Honourable Evan Solomon, Minister of Artificial Intelligence and Digital Innovation; Fahad Razak, internist at St. Michael’s Hospital and Canada Research Chair in Healthcare Data and Analytics at the University of Toronto; Philippe Després, Professor, Université Laval; Neesh Pannu, Vice Dean Research, Faculty of Medicine & Dentistry, University of Alberta; Karim Bardeesy, Member of Parliament for Taiaiako’n—Parkdale—High Park, Ontario; Melanie Woodin, President of University of Toronto; David Naylor, Chair of Vital Advisory Committee.

Ahead of Prime Minister Mark Carney’s federal government unveiling its long-awaited artificial intelligence strategy, Lisa Strug, University of Toronto Professor and Director of the Data Sciences Institute, joined Global’s Nivrita Ganguly to discuss what we can expect.