Logan Stapleton is a Ph.D. candidate at University of Minnesota. His current work focuses on how machine learning algorithms perpetuate discrimination and surveillance, as well as how technology and data science can support families impacted by the child welfare system.
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Devansh Saxena is a PhD candidate in the Department of Computer Science at Marquette University. His research focuses on studying algorithmic systems used in the public sector, especially the child welfare system. His current work examines collaborative child-welfare practice where decisions are mediated by policies, practice, and algorithms.
Anna Kawakami is a Ph.D. student in Carnegie Mellon University’s Human-Computer Interaction Institute. Her work focuses on understanding whether and how we could achieve human-AI complementarity in real-world, social decision-making domains. She is interested in using mixed and participatory methods to address questions related to model, interface, and organizational design.
Tonya Nguyen is a Ph.D. student in University of California, Berkeley’s School of Information. She designs and builds sociotechnical systems in high-stakes policy contexts and, she studies how embedded values in technology can change the way we self-organize and navigate political change. More broadly, her research is in the field of human-computer interaction, social computing, public interest technology, and new media.
Asbjørn Ammitzbøll Flügge is a Ph.D. student in the Department of Computer Science, at the University of Copenhagen. His research interest is in algorithmic systems in public services, in particular employment services. His current work focuses on how algorithmic systems impact caseworkers’ practices, as well as elderly job seekers perspectives on these technologies.
Motahhare Eslami is an assistant professor at the School of Computer Science, Human-Computer Interaction Institute (HCII), and Institute for Software Research (ISR), at Carnegie Mellon University. She earned her Ph.D. in Computer Science at the University of Illinois at Urbana-Champaign. Motahhare’s research goal is to investigate the existing accountability challenges in algorithmic systems and to empower the users of algorithmic systems, particularly those who belong to marginalized communities or those whose decisions impact marginalized communities, make transparent, fair, and informed decisions in interaction with algorithmic systems.
Naja Holten Møller is an Assistant Professor in the Department of Computer Science, at University of Copenhagen and founder of the Confronting Data Co-Lab. Her work centers on how data-driven technologies introduce continual forms of change to public sector decision-making processes, impacting citizens and non-citizens and other stakeholders who engage with these processes.
Min Kyung Lee is an Assistant Professor in the School of Information at the University of Texas at Austin. She directs a Human-AI Interaction lab at UT Austin, which aims to build more just and empowering workplaces and cities by creating technology that strengthens individual and collective human decision-making. Dr. Lee has conducted some of the first studies that empirically examine the social implications of algorithms’ emerging roles in management and governance in society. She has extensive expertise in developing theories, methods and tools for human-centered AI and deploying them in practice through collaboration with real-world stakeholders and organizations.
Shion Guha is an Assistant Professor in the Faculty of Information at the University of Toronto where he is part of the Critical Computing Group and directs the Human-Centered Data Science lab. His work centers on algorithmic decision-making and public policy with focus on child welfare, criminal justice and healthcare.
Kenneth Holstein is an Assistant Professor in Carnegie Mellon University’s Human-Computer Interaction Institute where he directs the CoALA Lab. His work explores human-AI complementarity, as well as how the design, development, evaluation, and oversight processes for human-algorithm decision systems can be improved in practice.
Haiyi Zhu is an Assistant Professor in Carnegie Mellon University’s Human-Computer Interaction Institute, where she directs the Social AI Lab. She is a social computing researcher and her research lies at the intersection of human-computer interaction, machine learning, and social psychology.
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