From investigating bird species to deepening our knowledge of the universe: meet U of T’s newest cohort of Schmidt AI in Science Postdoctoral Fellows

“We are grateful to Schmidt Sciences for developing and supporting this fellowship, which is allowing young scientists to take risks with new techniques to drive innovation,” says Lisa Strug, director of U of T’s Data Sciences Institute and co-lead of the Schmidt AI in Science Postdoctoral Fellowship program.

Since U of T welcomed its first cohort of 10 Schmidt Science Fellows in 2023, almost all have completed their two-year fellowship, with a collective accomplishment of 36 publications and 49 conference presentations. Now, the second group of 10 researchers have started their fellowships over the past several months, and there is a great deal of excitement surrounding their work and what they hope to achieve.

“Equipped with AI tools and training that will transform and accelerate their research, the sky is the limit for this talented group of scientists as they work on novel solutions to the daunting global challenges we’re facing,” says Alán Aspuru-Guzik, director of U of T’s Acceleration Consortium and co-lead of the Schmidt AI in Science Postdoctoral Fellowship program.

Introducing the second cohort

Biprateep Dey: In his study “Connecting the Light and Dark Sides of Galaxy Formation,” Dey is using AI to predict galaxy distances directly from images and apply statistical techniques to explore correlations between galaxies and their neighbours – all of which will help us better understand how galaxies form and evolve. Under the supervision of Assistant Professor Joshua Speagle, Dey is working in the Department of Statistical Sciences on St. George Campus.

David Pellow: Pellow is using AI and machine learning to develop prediction models for capturing unique biological indicators of adverse liver outcomes through his study “Machine Learning models for improving liver disease.” He is working in the Department of Computer Science on St. George Campus under the supervision of Professor Michael Brudno.

Duo Xu: Through his study “Unraveling Star Formation with Artificial Intelligence,” Xu is using advanced machine learning techniques to bridge the gap between simulations and real astronomical observations, with the ultimate goal of better understanding the complex factors that drive star formation and deepening our insight into the universe. He’s working in the Canadian Institute for Theoretical Astrophysics (CITA) on St. George Campus under Professor Peter Martin and Assistant Professor Joshua Speagle.

Matthew Thorstensen: Exploring the question of why there are so many different tropical birds, Thorstensen’s study is titled “Deep learning, evolution, and species richness: Why do some regions have so many species?” He is using AI to address whether natural selection may have fluctuated with past glacial cycles in northern areas, and if environmental changes over time were less pronounced in the tropics. Working in the Department of Biological Sciences at University of Toronto Scarborough, his supervisor is Professor Jason Weir.

Mehdy Dousty: Dousty uses machine learning to predict falls among the elderly using wearable and non-wearable technology. Through his study “Gait analysis using radio frequency signals,” he plans to develop deep learning models to estimate 3D joint coordinates, predict the risk of falls within specific timeframes and create a heatmap of “fall likelihood” within homes. He’s working in the Department of Electrical & Computer Engineering on St. George Campus under Professor Ervin Sejdic and Professor David Fleet.

Yilun Guan: By measuring cosmic microwave background (CMB) radiation, scientists have gained a deeper understanding of the universe, and the Simons Observatory in Chile aims to further refine this understanding by producing a map of the CMB sky with unparalleled precision. But this poses significant challenges, as even small errors can contaminate the data. Through his study “Enabling the most sensitive measurement of cosmic birth with AI,” Guan is developing and applying advanced AI technologies to address these challenges. He’s working in the Department of Astronomy & Astrophysics on St. George Campus under Associate Professor Renee Hlozek and Assistant Professor Adam Hincks.

Zhewei Liu: In his study “Unpacking environmental injustice faced by North American vulnerable populations due to climate change,” Liu uses AI to better understand and mitigate the exposure risks and disparities stemming from environmental hazards within vulnerable communities. Under the supervision of Assistant Professor Jue Wang, Liu is working in the Department of Geography, Geomatics and Environment at University of Toronto Mississauga.

Mandate for building strong community

Building a strong, lifelong community among the Schmidt Fellows is a key priority of the program – and to that end, the second cohort has energized the program with their collective enthusiasm for engagement and connection, embracing a wide range of technical, professional and social activities at U of T.  

To strengthen their AI knowledge and skills, they’ve begun participating in a number of technical training sessions, including machine learning tutorials and bootcamps with U of T’s Centre for Analytics and Artificial Intelligence Engineering (CARTE).

On a professional level, they’re engaging with each other and U of T’s larger postdoc community through various mixer events (including with the Vector Institute for Artificial Intelligence postdocs), networking lunches and professional development sessions. Half of the newest cohort even attended the 2025 Global Young Scientists Summit in Singapore together in January, giving them an opportunity to showcase their leadership skills and represent U of T on the international stage.

And of course, social connection is essential to building a strong community – and members of this newest cohort have already taken the initiative to organize several social activities among the group. “With many of our Cohort 2 Fellows coming to Toronto from outside of Canada, it has been amazing to see how they’re finding connection with each other while exploring Toronto’s attractions and diverse food scene,” says Amanda Mohabeer, program manager, Schmidt AI in Science Postdoctoral Fellowship program. “With more cross-program networking events and off-campus social engagements in the works, we plan to keep this momentum going.”