Schwartz Reisman Institute announces 2026–27 graduate fellows
The Schwartz Reisman Institute for Technology and Society is pleased to announce its cohort of 2026–27 graduate fellows, bringing together fifteen exceptional U of T researchers exploring the societal implications of AI and emerging technologies.
The Schwartz Reisman Institute for Technology and Society (SRI) is proud to announce its 2026–27 cohort of graduate fellows. Hailing from across the University of Toronto, fifteen outstanding students will join SRI’s interdisciplinary research community, dedicated to shaping technologies that serve the public good.
The new cohort brings together researchers working across computer science, information studies, psychology, law, medicine, management, industrial relations, and history. Their projects reflect the breadth of contemporary questions surrounding the beneficial use of artificial intelligence (AI) and emerging technologies—from governance, accountability, and privacy to health, accessibility, labour, creativity, and democratic life.
“Addressing the societal implications of AI requires collaboration across disciplines, perspectives, and lived experiences,” said SRI Director David Lie. “This year’s cohort reflects the remarkable breadth of research taking place across the University of Toronto, and we are excited to support these scholars as they advance new approaches to responsible, human-centered technology.”
The 2026–27 Schwartz Reisman Institute graduate fellows are:
Leif Anderson, PhD student, Department of Psychology
Sara Bocchinfuso, Master’s student, Institute of Health Policy, Management & Evaluation
Marco Germanò, SJD candidate, Faculty of Law
Md Arid Hasan, PhD student, Department of Computer Science
Sophia Jit, PhD student, Department of Computer Science
Dariia Kucheruk, PhD student, Department of Computer Science
Patrick Yung Kang Lee, PhD student, Department of Computer Science
Azhagu Meena, PhD student, Faculty of Information
Shawn Meikle, PhD candidate, Centre for Industrial Relations & Human Resources
Rowan O.A. Munson, PhD student, Faculty of Information
Gemma Postill, MD/PhD candidate, Institute of Health Policy, Management & Evaluation
Benjamin Pulver, PhD candidate, Graduate Department of Art History
Frieda Rong, PhD student, Department of Computer Science
Tracy Zhang, PhD candidate, Graduate Department of Pharmaceutical Sciences
Xingjian (Ken) Zhang, PhD candidate, Joseph L. Rotman School of Management
SRI graduate fellowships support interdisciplinary research that examines the complex relationships between technology and society. Through the program, fellows engage with a cross-disciplinary network of researchers, participate in Institute programming, and contribute to conversations shaping the future of responsible technology development and governance.
Get to know SRI’s 2026–27 graduate fellows
Leif Anderson is a PhD student in the Department of Psychology at the University of Toronto Scarborough, where he works with Y. Andre Wang in the Attitudes & Interpersonal Understanding (AIU) Lab. His research examines how people reason about empathy, including how individuals evaluate empathizers, the moral boundaries people place around empathy, and the forms of empathy people want to receive from both humans and AI systems. Anderson is particularly interested in the responsible design of empathic AI and how emotionally responsive systems shape social relationships, emotional wellbeing, and belief formation.
Sara Bocchinfuso is a graduate student in Clinical Epidemiology and Health Care Research (CEHCR) at the University of Toronto and a General Surgery resident at the Mayo Clinic. Her research focuses on survivorship care following gastric cancer treatment, using population-based data to evaluate long-term care delivery and identify gaps in nutrition surveillance and support. She is investigating the responsible use of AI-assisted evidence synthesis, with a particular focus on applying large language models to systematic review workflows such as study screening and data extraction. Her work bridges surgical oncology, clinical epidemiology, and the ethical integration of AI into healthcare research and decision-making.
Marco Germanò is a doctoral researcher (SJD) at the University of Toronto’s Henry N.R. Jackman Faculty of Law whose research examines how legal and technological systems can be designed to advance public interests during periods of institutional transformation. His work explores questions of AI alignment, legitimacy, sovereignty, and institutional governance, with particular attention to how algorithmic systems reshape the procedural and normative foundations of public authority. Germanò has held academic and professional appointments with organizations including the United Nations, the University of Oxford, NYU School of Law, Peking University, and the University of São Paulo. He currently serves as a Legal Advisor at the UN International Law Commission and as a Research Affiliate at NYU School of Law’s Guarini Global Law & Tech initiative.
Md Arid Hasan is a PhD student in the Department of Computer Science at the University of Toronto specializing in natural language processing, human-centered AI, and AI for wellbeing. His research focuses on large language models, multilingual and low-resource NLP, and culturally grounded AI systems, with particular emphasis on how AI technologies reproduce or challenge existing epistemic inequalities. Hasan has contributed to research on LLM evaluation, culturally aware question answering, and language technologies for low-resource communities, with publications in venues including ACL, EMNLP, and COLING.
Sophia Jit is a PhD student in the Department of Computer Science at the University of Toronto supervised by Professors Marsha Chechik and Lina Marsso. Her research lies at the intersection of trustworthy AI, requirements engineering, human-computer interaction, and computational social science. Working in collaboration with legal scholars and industry partners, she develops methods for translating normative and legal rules into machine-interpretable guardrails for AI systems operating in high-stakes contexts. Her work has appeared in leading venues including CHI, Nature Communications, FSE, RE, and COMPASS, and she has presented her research to municipal and federal government agencies in Canada.
Dariia Kucheruk is a PhD student in the Department of Computer Science at the University of Toronto whose research focuses on machine learning methods for healthcare and biomedical applications. Her work integrates structured scientific knowledge—including anatomical and genetic relationships—directly into AI model design to improve interpretability, robustness, and trust in high-stakes settings. Kucheruk’s research spans machine learning, computer vision, and computational biology, including projects on neonatal brain MRI segmentation and biologically grounded generative modelling of craniofacial structure from genetic data. She is also actively involved in mentorship, outreach, and initiatives supporting broader participation in computing.
Patrick Yung Kang Lee is a PhD student in the Department of Computer Science at the University of Toronto and a Junior Fellow at Massey College. His research sits at the intersection of human-computer interaction, social computing, and AI ethics, focusing on the social and ethical implications of anthropomorphic AI systems, including AI companions, mimetic models, and AI replicas. Drawing on qualitative and ethnomethodological approaches, Lee studies how people form relationships with increasingly human-like AI systems and how these systems reshape interpersonal norms, trust, and belonging.
Azhagu Meena is a doctoral researcher in the Faculty of Information at the University of Toronto supervised by Negin Dahya. Her work examines how digital technologies reflect and reproduce social values, with a particular focus on designing more equitable and culturally grounded systems. Through a postcolonial feminist lens, her current research investigates mental health chatbots and large language models in relation to Indian working mothers, asking how such systems might better center marginalized forms of knowledge and lived experience.
Shawn Meikle is a PhD candidate at the Centre for Industrial Relations and Human Resources at the University of Toronto, and is the recipient of an SRI–PAIQ Graduate Fellowship, co-sponsored by the Partnership on AI and Quality of Work initiative at the Institute for Work & Health. Meikle’s research explores the relationship between technological change, labour power, and workplace safety, with a particular focus on how AI systems are reshaping occupational health and safety in industrial settings. Alongside his academic work, Meikle is also a practicing union millwright working on industrial, commercial, and institutional construction projects across the Greater Toronto Area.
Rowan O.A. Munson is a PhD student in the Faculty of Information at the University of Toronto whose research investigates how designers’ worldviews shape technological systems. Drawing on science and technology studies, human-computer interaction, and participatory research methods, Munson explores how shifting from assumptions of separateness toward models of interconnectedness between people, place, and planet can support more socially just and sustainable technologies. He is also the creator of “Save the AI,” a satirical project examining the environmental and social costs of contemporary AI systems, and has previously worked across public policy, advocacy, and social research in the United Kingdom.
Gemma Postill is an MD/PhD candidate at the University of Toronto’s Clinical Epidemiology and Health Care Research (CEHCR) whose research focuses on artificial intelligence in healthcare. Her work develops and evaluates machine learning approaches for personalized prognostication after severe injury, with the goal of supporting more individualized and patient-centered clinical decision-making. Postill is particularly interested in how AI systems can better account for long-term recovery trajectories and outcomes that matter to patients. In addition to her research, she serves as student education co-lead at the Temerty Centre for AI Research and Education in Medicine (T-CAIREM), where she contributes to educational initiatives focused on the responsible and human-centered integration of AI in healthcare.
Benjamin Pulver is a PhD candidate in the University of Toronto’s Graduate Department of Art History whose research examines the political, technological, and aesthetic conditions shaping AI-generated imagery and computational creativity. Drawing on cybernetics, information theory, aesthetics, and philosophy of mind, his work explores how generative AI systems are reshaping cultural production and contemporary understandings of creativity and intelligence. Pulver is also a Junior Fellow at Massey College and a Graduate Research Fellow at the Centre for Culture and Technology.
Frieda Rong is a PhD student in the Department of Computer Science at the University of Toronto researching safety evaluation methods for self-driving vehicles. Her work focuses on testing, simulation, and scenario-based evaluation techniques for autonomous driving systems, with the goal of improving reliability and communication between vehicles and vulnerable road users. Prior to her doctoral studies, Rong worked at both Waabi and Uber Advanced Technologies Group, and her research on data-driven sensor simulation for autonomous driving was recognized as a Best Paper Candidate at CVPR 2021.
Tracy Zhang is a PhD candidate in the Graduate Department of Pharmaceutical Sciences at the University of Toronto supervised by Zubin Austin. Her research examines how different stakeholder groups—including healthcare professionals, patients, and technology developers—conceptualize risk in relation to AI systems used in healthcare. By studying how professional identities and institutional contexts shape understandings of risk, Zhang’s work aims to inform proportionate and trustworthy approaches to AI regulation in clinical settings. She brings more than a decade of experience as a practicing pharmacist providing direct patient care across a range of healthcare environments.
Xingjian (Ken) Zhang is a PhD candidate in Strategic Management at the University of Toronto’s Rotman School of Management supervised by András Tilcsik. His research investigates how audiences respond to disclosures of generative AI use across professional and creative domains. Combining experimental and econometric methods, Zhang studies how AI disclosures shape trust, credibility, and evaluations of AI-assisted work in settings such as financial analysis and crowdfunding. His work aims to better understand the strategic and social dimensions of transparency in human-AI collaboration.
About the SRI graduate fellowship program
SRI’s graduate fellowship program is a core part of the Institute’s mission to support emerging scholars whose work bridges disciplinary boundaries and advances critical research on the societal implications of advanced technologies. Fellows join a growing interdisciplinary community at the University of Toronto committed to addressing the ethical, political, cultural, and technical dimensions of AI and related technologies.
Throughout the fellowship year, fellows will participate in SRI programming, contribute to interdisciplinary exchange across the Institute, and share their research through public events, collaborative initiatives, and community engagement activities.
Want to learn more?
Browse stories by tag:
- AI
- AI safety
- AI trust
- Computer science
- Computer security
- Copyright
- Cybersecurity
- Data
- Democracy
- Economics
- Education
- Engineering
- Ethics
- GPO-AI
- Governance
- Health
- Human Rights
- In the Media
- Jobs
- LLMs
- Law
- Normativity
- Philosophy
- Political Science
- Privacy
- Privacy Series
- Psychology
- Public Policy
- Recommenders
- Regulation
- Religion
- Reports
- Trust
- Workshops
