Schwartz Reisman Institute announces 2024 fellowship recipients
The Schwartz Reisman Institute for Technology and Society is proud to welcome four new faculty fellows and 15 graduate fellows from across the University of Toronto. SRI fellowships support interdisciplinary research that builds new approaches to examine the complex relations between technology and society.
The Schwartz Reisman Institute for Technology and Society (SRI) is proud to announce the recipients of its 2024 call for faculty and graduate fellowships. Four faculty members and 15 graduate students from the University of Toronto's research community have been appointed as Schwartz Reisman Institute fellows and will help advance the Institute’s mission to ensure that advanced technologies benefit all of society.
The incoming fellows bring a wide range of research interests, spanning medicine, psychology, economics, political science, computer science, philosophy, engineering, information studies, environmental science, and anthropology. Their diverse expertise will help enrich SRI’s interdisciplinary environment and support the development of human-centered approaches towards the effective governance of advanced technologies.
Schwartz Reisman Institute fellowships are designed to support interdisciplinary research that explores the complex relationships between technology and society, bridging academic disciplines and developing innovative applications to enhance social good.
The 2024 cohort of SRI fellows increases the total number of U of T scholars who have received SRI fellowships to more than 100 to date, with more than $1 million awarded in support of innovative interdisciplinary research projects.
Left to right: University of Toronto faculty members Zubin Austin, Felix Cheung, Kristina McElheran, and Semra Sevi are recipients of 2024–26 SRI Faculty Fellowships. Supplied images.
2024–26 Schwartz Reisman Institute faculty fellows
Zubin Austin, professor, Graduate Department of Pharmaceutical Sciences
Felix Cheung, assistant professor, Department of Psychology
Kristina McElheran, assistant professor, Department of Management, University of Toronto Scarborough (UTSC)
Semra Sevi, assistant professor, Department of Political Science
Zubin Austin is a professor in U of T’s Graduate Department of Pharmaceutical Sciences with a cross-appointment at the Temerty Faculty of Medicine’s Institute for Health Policy, Management, and Evaluation. Austin is an international leader in the area of bridging education for international professionals, and is regularly commissioned by regulatory bodies in Canada, the U.S., the U.K., and Australia to study competency-related issues. Austin’s fellowship project, “Regulatory Guardrails for Adoption and Implementation of AI Technologies in Health Care,” expands his recent work on the regulation of complex problems by seeking to understand AI implementation in healthcare from the perspective of regulators as healthcare practitioners, and will consider what safeguards are required as AI technologies shift certain types of healthcare work towards more independent, human-out-of-the-loop activities.
Felix Cheung is an assistant professor in U of T’s Department of Psychology and a Canada Research Chair in Population Well-Being. Cheung runs the Population Well-Being Lab at U of T, where his research examines the determinants and consequences of subjective well-being, with a focus on pressing global issues such as sociopolitical unrest and inequality. Cheung’s fellowship project, “The Global Impact of Industrial Robots on Societies,” will be the first large-scale global study on the well-being impact of industrial robotics from a human-centered perspective. Using data from one million participants across 67 countries, he will test whether industrial automation brings net benefits to societies and document how it may lead to disparities in well-being.
Kristina McElheran is an assistant professor in the Department of Management at UTSC, with a cross appointment at the Rotman School of Management. Trained in managerial economics and strategy, her research explores how data and information technologies can enable firms and workers to thrive in the digital age, with a growing focus on entrepreneurship and the future of work. Recently, McElheran and her collaborators found AI adoption is unevenly distributed in the U.S., with fewer than six per cent of firms using AI technologies, foreshadowing a growing divide between large and small firms. McElheran’s fellowship project, “AI for an Inclusive Future of Work,” will explore how algorithmic nudges from large language models (LLMs) may promote more inclusive hiring and job design.
Semra Sevi is an assistant professor in the Department of Political Science whose research explores voting behaviour, political representation, public opinion, legislative politics, women in politics, and partisanship. Sevi’s fellowship project, “Do Chatbot Voting Aid Applications Help Young Independent Voters Embrace a Party?,” seeks to train a novel AI-assisted voting aid application chatbot on party platforms, and will measure whether interactions between this chatbot and youth who do not identify with a political party can help unaffiliated voters to embrace a political party and increase electoral participation.
Left to right, top to bottom: University of Toronto graduate students Ananya Bhattacharjee, Jessica Bo, Joshua Brecka, Manuela Collis, Micaela Elisa Consens, Rebekah Gelpí, Cristina Getson, Ben Li, Madison Mackley, Erina Moon, Emmanuel Taiwo, Balagopal Unnikrishnan, Joseph Wilson, Siyi Wu, and Fernando Yánez are recipients of 2024–25 SRI Graduate Fellowships. Supplied images.
2024–25 Schwartz Reisman Institute graduate fellows
Ananya Bhattacharjee, Department of Computer Science
Jessica Bo, Department of Computer Science
Joshua Brecka, Department of Philosophy
Manuela Collis, Rotman School of Management
Micaela Elisa Consens, Department of Computer Science
Rebekah Gelpí, Department of Psychology
Cristina Getson, Department of Mechanical & Industrial Engineering
Ben Li, Institute of Medical Science
Madison Mackley, Faculty of Information
Erina (Seh-Young) Moon, Faculty of Information
Emmanuel Taiwo, Department of Physical & Environmental Sciences
Balagopal Unnikrishnan, Department of Computer Science
Joseph Wilson, Department of Anthropology
Siyi Wu, Department of Computer Science
Fernando Yánez, Department of Computer Science
Ananya Bhattacharjee is a PhD candidate in the Department of Computer Science whose research focuses on understanding the role of technology and human-AI collaboration in supporting individual and social well-being. His fellowship project will develop group-level interventions to address challenges of residual mobility among international migrants, blending social theories and technology to foster a more inclusive social environment.
Jessica Bo is a PhD student in the Department of Computer Science whose research focuses on human-centered approaches to designing and evaluating human-AI interactions, with a particular emphasis on understanding behaviours and attitudes towards generative AI models such as LLMs. Her fellowship project explores how transparency and explainability tools can help users develop better understandings of AI capabilities, and methods to foster appropriate reliance and trust in AI technologies.
Joshua Brecka is a PhD candidate in the Department of Philosophy whose research explores the nature and epistemic role of trust, including how trust is enacted between individuals, groups of experts, and organizations such as corporations and governments. His fellowship project seeks to develop and defend a novel philosophical account of trustworthy AI, based on how worthy a given system is of being incorporated into one’s cognitive agency.
Manuela Collis is a PhD candidate at the Rotman School of Management whose past research explores how gender inequalities shape organizational outcomes and innovation. In her fellowship project, “The Value of Human Skill and Talent,” Collis will investigate the economic and social impacts of automating human abilities and capacities. Rather than asking what forms of labour are susceptible to automation, Collis’s project explores what human values are of such significance and importance that they should not be automated.
Micaela Elisa Consens is a PhD candidate in the Department of Computer Science, a Vector Institute graduate affiliate, and an NSERC Scholar. Her research develops novel computational methods to investigate biological questions regarding human molecular machinery. Consens’s fellowship project will enhance the interpretability of transformer-based genomic models using Layer-wise Relevance Propagation (LRP), attention analysis, and GPT-4 prompting to better understand how attention heads contribute to model decisions, and interpret these contributions in a biologically meaningful way.
Rebekah Gelpí is a PhD candidate in the Department of Psychology and a graduate affiliate at the Vector Institute. Her research investigates the origins and development of emergent social behaviours, such as coordination, convention formation, categorization, inequality, and stereotyping. Using tools such as LLMs and multi-agent reinforcement learning, Gelpí develops models that capture how groups of individuals create emergent, complex behavioural dynamics. Her project seeks to establish a social cognitive benchmark for LLMs that enables better understandings of their latent representations of social cognition and characterizes their similarities and differences to human social cognitive reasoning.
Cristina Getson is a PhD candidate in the Department of Mechanical & Industrial Engineering whose research focuses on how the well-being of vulnerable populations, such as older adults and those with cognitive impairments, can be improved through human-robot interactions. Working at the intersection of engineering, psychology, and design, Getson designs socially assistive robots that can provide long-term benefits to those who provide care and those in need of care. Her project will develop a novel learning framework for a socially assistive robot to adapt its interaction behaviour strategies to motivate and engage vulnerable populations in order to help maintain their cognitive skills.
Ben Li is a vascular surgery resident and PhD student at the Institute of Medical Science. His research focuses on using machine learning to predict outcomes in patients undergoing major vascular surgery. Li has published over 50 papers, given over 50 conference presentations, and received over 30 grants/awards totalling over $700,000. As an SRI graduate fellow, Li hopes to work at the intersection of health and technology to improve care for patients living with vascular disease.
Madison Mackley is a PhD student in the Faculty of Information whose research examines existing and emergent data governance models within the Canadian public sector. Through collaborative research with government institutions and civic organizations, her fellowship project seeks to uncover sites of innovation that illustrate how new data governance mechanisms might facilitate data-sharing while protecting individual and collective rights.
Erina (Seh-Young) Moon is a PhD student in the Faculty of Information whose research focuses on the interdisciplinary field of human-centred data science. Combining technical methodologies with interpretive methods, Moon studies the intersection between data science, public policy, and human-computer interaction. Her fellowship project explores the design of fair AI decision-support tools that support frontline staff who serve the unhoused in Canada, incorporating stakeholder perspectives from homeless support service providers in Toronto to examine whether AI decision-making tools can mitigate structural inequalities.
Emmanuel Taiwo is a chartered environmentalist undertaking a PhD in environmental science at UTSC’s Department of Physical & Environmental Sciences. Taiwo’s research focuses on just climate and energy transitions, investigating and tackling barriers preventing adoption of low-carbon energy technologies and innovations by marginalized communities. He has advised Global Affairs Canada on equitable climate transitions, and the U.K. government on climate and environmental matters in Nigeria, where he led a £66 million U.K.-funded program which provided clean energy access for millions of underserved people. Through his fellowship, Taiwo aims to explore critical linkages between frontier technologies such as artificial intelligence and equitable climate, energy, and environmental transitions.
Balagopal Unnikrishnan is a PhD student in the Department of Computer Science, where his research is also supported by the Vector Institute, University Health Network (UHN), and SickKids Hospital. Unnikrishnan’s research interests lie at the intersection of AI, machine learning, and healthcare, with a primary focus on understanding and mitigating shortcut learning and data bias in healthcare data. His fellowship project will develop algorithms for bias mitigation to improve the robustness of AI models on radiology and ultrasound data.
Joseph Wilson is a PhD candidate in the Department of Anthropology, Linguistic & Semiotic stream, whose research examines how scientists communicate with one another and with external stakeholders as they build theory together. He has written widely on AI, language, and anthropology for mainstream media outlets and has taught at York University, Trent University, and U of T’s School of Continuing Studies. Wilson co-founded the Education Cluster at the MaRS Discovery District and has produced conferences, exhibitions, and curricula for the Ontario Science Centre, Royal Ontario Museum, and American Museum of Natural History. His fellowship will explore how AI scientists make sense of their work, collaborate across disciplines, and communicate with investors, policy-makers, and media.
Siyi Wu is a PhD student in the Department of Computer Science, whose research interests are climate informatics, human-computer interaction, and explainable AI. Her fellowship project explores the applications of explainable AI in climate science, focusing on how climate scientists envision using machine learning and climate risk communications. Wu’s research advocates for direct engagement of various stakeholders to develop tailored solutions addressing specific user needs and concerns, and aims to design AI models and interpretable techniques aligned with human values.
Fernando Yánez is a PhD student in the Department of Computer Science whose research involves developing dynamic data visualizations that adjust to the cognitive and educational needs of users. His fellowship project will develop user-adaptive visualizations that are able to cater to the unique learning needs and preferences of individual students, aiming to make educational content more accessible and effective, and bridging gaps in equity and inclusivity by enhancing learning experiences for diverse student populations.
