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Professor Nancy Reid, one of North America’s foremost statisticians, is being honoured this fall with the naming of a flagship lecture series.

The Distinguished Lecture in Statistical Sciences (DLSS) has, since 2000, brought top scholars in statistical sciences to Toronto to share their research with academic and broader audiences. The series’ new name, the Nancy Reid Distinguished Lecture in Statistical and Data Sciences, honours Professor Reid’s scholarship, her contributions to the University of Toronto, and her influence in the international research community.

Trained at the University of Waterloo, the University of British Columbia, and Stanford University, Professor Reid began her career with a postdoctoral fellowship as a NATO scholar at Imperial College London. As a faculty member appointed to UBC’s Department of Mathematics, Professor Reid was a founding member of their Department of Statistics and helped to design the new undergraduate and graduate statistics programs. In 1986 she joined the University of Toronto Department of Statistical Sciences, where she is now University Professor Emeritus. Throughout her career, Professor Reid has received numerous honours and awards, including appointment as Officer of Order of Canada, and election to Fellow of the UK Royal Society, the Royal Society of Canada, and the Royal Society of Edinburgh.

Professor Reid played a pivotal role in the establishment and early development of the Canadian Statistical Sciences Institute (CANSSI). In 2010, she chaired a Natural Sciences and Engineering Research Council of Canada steering committee, whose recommendations included the creation of CANSSI. She went on to serve as the Institute’s second Scientific Director, helping to advance its mission of strengthening statistical sciences research and collaboration across Canada.

When Professor Reid was selected for and delivered the 2025 DLSS, she joined a select group of internationally renowned scholars from prestigious institutions from around the world. Her participation, however, extends well beyond her role as a lecturer. Professor Reid has been closely involved with the series since its inception, when it was first hosted at the Fields Institute for Research in Mathematical Sciences.

Professor Reid recalls working with Professor Donald Dawson, then director of the Fields Institute, who proposed establishing the lecture series. “Don wanted to broaden the Fields Institute’s reach to include the statistical sciences,” she explains. She also recalls that Peter Hall, then at the Australian National University, had delivered a series of lectures before the formal establishment of the DLSS. “We decided to recognize him retrospectively as the inaugural lecturer.”

Over time, the DLSS grew to involve a larger group of organizers, with Professor Reid continuing to play a central role. Since 2019, the series has been hosted by the Ontario regional center of CANSSI and has retained its format of two lectures: one general and one more specialized lecture delivered by an internationally prominent scholar.

Mary Thompson, Distinguished Professor Emerita in the University of Waterloo’s Department of Statistics and Actuarial Science, and CANSSI’s founding Scientific Director, reflects on Professor Reid’s influence:

“Nancy Reid has been a defining figure in Canadian Statistical Sciences, in CANSSI’s history, and in the history of this lecture series. As we embark on this new chapter in the lectureship, it is fitting that the series carry Professor Reid’s name as a reflection of her stature in our community and in our field.”

Along with its new name, a renewed vision for the Lecture will broaden the series’ scope to encompass both statistical and data science, building on Professor Reid’s advocacy for collaboration and for the importance of statistical thinking to advance real world problems.

Professor Reid reflects on how statistical science, machine learning, data science and AI have become increasingly interconnected over time. “There has always been a valuable exchange between statisticians and machine learning researchers. At its core, machine learning is statistical, but with larger datasets, more computing power, and a greater emphasis on prediction.”

With the emergence of data science, Professor Reid observes a shift in focus in statistical science to the entire data lifecycle, from collection to application to communication. “Traditionally, statisticians were often brought in to analyze data that others had collected. Data science expanded that role to include collecting, linking and preparing the data, defining answerable questions, interpreting the results, and informing decisions. Statistics remained central, but the scope of our work grew. In the early to mid-2000s, for example, the Department of Statistical Sciences at U of T made several joint faculty hires in fields such as environmental science, philosophy, sociology and information science. As more disciplines began collecting and working with large amounts of data, statistics increasingly looked outwards.”

Professor Sebastian Jaimungal, chair of the University of Toronto Department of Statistical Sciences in the Faculty of Arts & Science, says, “Nancy Reid has played an extraordinary role in shaping Statistical Sciences in Canada and beyond. We are fortunate to have had her as a colleague at the University of Toronto for so much of her distinguished career. Naming this lecture series in her honour is a fitting recognition of her remarkable contributions and a wonderful way to ensure her legacy continues to inspire future generations of researchers.”

Looking to the future, Professor Reid hopes the lectureship will continue to inspire new generations of scholars, just as encounters with exceptional minds helped shape her own intellectual journey. “I was fortunate to meet many remarkable people early in my career, and those encounters left a lasting impression on me. I hope the lectureship continues to bring together people with different perspectives, sparking new ideas, and inspiring faculty, students, and others in ways that will stay with them throughout their careers.”

How do you know who is coming through your front door? Up to a million people visit the Art Gallery of Ontario every year, and while the AGO aims to reach a wide audience, they need to know who is visiting to know if those targets are being met. Data collected through three years of visitor surveys and analyzed for the first time this summer as part of a collaboration between the AGO and the Data Sciences Institute offered a new opportunity for insight into visitor behaviour and experience.

Collaborations like this are key to DSI’s mission to accelerate the impact of data sciences and AI across disciplines to address pressing societal questions and drive positive social change. This project brought together undergraduate student Daniel Sun, faculty supervisor Jesse Gronsbell (Department of Statistical Sciences, Faculty of Arts & Science, University of Toronto) and the Visitor Experience and Development teams at the AGO, including Camellia Kazi, Assistant Manager, Visitor Experience Operations and Systems and Heman Lo, Senior Director, Visitor Experience and Commercial Enterprises.

The summer undergraduate data science experience (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. Now in its fifth summer, SUDS has supported more than two hundred research projects. Each project is led by a faculty supervisor, enabling more than three hundred undergraduate students to gain research experience in data science and AI.

The project with the AGO involved applying data science methods and developing analytical tools to analyze over 10,000 survey responses to questions around visitor identity. A visitor profile dashboard now provides AGO staff with interpretable statistics and visualizations. They can now see at a glance, for example, that satisfaction with the AGO increases with age, autumn is the highest performing season, and overall visitor satisfaction is very consistent over time.

Further analysis offered a chance to check the visitor profiles created by the AGO to target who they are hoping to reach, against clusters in the survey response data to questions about visitors’ identities. These clusters form meaningful and data-driven visitor profiles based on groups with similar features. Overlap between the personas and clusters suggests that the AGO’s intended audiences align with the audiences represented in the survey data.

For SUDS Scholar Daniel Sun, this was a very exciting opportunity to put into practice everything he’s learned about data science. “A lot of the data I work with in classes are numerical, but all the data I worked with at the AGO was categorical, so I really got to learn new methodologies. I also learned how to communicate data science and statistics to people who want to hear it in less technical terms .”

By analyzing this data, the project identified patterns in visitor behavior and barriers to engagement. Actionable insights like this help to support data-informed strategies for audience development and inclusive visitor experiences. By enabling the AGO to better understand how diverse audiences interact with exhibitions and programs, the project is contributing to improving accessibility, outreach, and cultural participation across communities.

This is an example of the kinds of projects that will be supported by the new Data Science & AI for Social Good stream.

Professor Jesse Gronsbell (Department of Statistical Sciences, Faculty of Arts & Science, University of Toronto) says, “SUDS is a wonderful chance for students to learn from, and work with, practitioners in different settings who bring their own data puzzles and needs.”

Camellia Kazi, Assistant Manager, Visitor Experience Operations and Systems, says “Not everyone thinks of data when they think of art galleries, but this project brought many valuable insights. We were very glad to collaborate with the Data Sciences Institute on this summer project.”

This summer, the Data Sciences Institute (DSI) partnered with the King Abdullah University of Science and Technology (KAUST) Academy to provide 12 exceptional Saudi scholars with the opportunity to engage in cutting-edge data science research in the 2026 cohort of the Summer Undergraduate Data Science (SUDS) Research Program.

SUDS provides a rich summer training experience for students from a wide variety of academic backgrounds to be exposed to and apply data science techniques in their work. International institutions can partner with DSI to have their students participate in SUDS. The international partner institution matches students with projects aligned with the partnering institutions’ research interests based on the Scholars’ skills, interests and expertise. SUDS International scholars travel to Toronto, stay in on-campus housing, participate in SUDS Cohort Programming, and are paired with other SUDS scholars from Canadian institutions.

This is the third year of DSI’s partnership with KAUST, with 14 KAUST students participating in 2024 and 27 in 2025. These scholars, recipients of prestigious awards from KAUST, are selected through a highly competitive process, ensuring that only the highest performing students were chosen to represent the Kingdom on a global stage.

Sulaiman Alangari worked with Professor Renee Hlozek of the David A. Dunlap Department of Astronomy and Astrophysics in the Faculty of Arts and Science on his project Toward SED reconstruction of Type la Supernovae with Rubin Observatory Simulations. “This was my first time studying abroad,” he said, “and it was a new experience for me to work on a research project in one of the biggest universities and institutes. It was a very informative experience, and I learned a lot about the research industry and how to read and conceptualize research papers.”

Eshraq Yahya Zakri worked with Professor John Morris of the Terrence Donnelly Centre for Cellular and Biomolecular Research in the Temerty Faculty of Medicine on her project, A Variant-Centric Pipeline for Functional Annotation and Trait Association Analysis. She said, “My summer was great. I loved the work we were doing and I thought it was very important that we were connected to other groups. My experience in the lab was great, everyone was so motivated and I learned a lot.” 

Professor Zahra Shakeri, of University of Toronto Institute of Health Policy, Management, and Evaluation, supervised three KAUST students, Nawaf Alahmed, Nasser Altamimi, and Abdullah Bukhari, alongside U of T student Fang Sheng on the project Mechanistic Analysis of Template-Injection Jailbreaks in Diffusion Language Models. Prof. Shakeri described her experience working with the KAUST students, “I was very impressed by how much they contributed technically in such a short period. They were involved from the first week and came prepared to every update meeting and internal presentation. What stood out to me was how quickly they became part of the lab and started contributing like regular team members. The projects were technically demanding, but the students handled the work at a level that exceeded my expectations for a short summer placement.”

The students’ contribution has also continued beyond the program, Prof. Shakeri says. “They are still working with us to complete the final stages of the projects and prepare the work for manuscript submission. Their work was also recognized at the showcase with the Best Poster Award. I would be very glad to work with KAUST students again.”

Professor Lisa Strug, director of the Data Sciences Institute, says, “We are very proud of our ongoing partnership with KAUST. Over these past three years, we have welcomed some incredible young scholars to Toronto. As Canada and the University of Toronto continue to lead in AI and data science, international collaborations like this one are all the more impactful.”

The University of Toronto is a world-leading university in the heart of a global city. SUDS students – from U of T and beyond – come from all around the world. DSI welcomes international institutions to connect with us at partnerships.dsi@utoronto.ca to learn more about partnerships through SUDS International.