I am an Assistant Professor at the University of Wisconsin-Madison The Information School, where I lead research at the intersection of Human-Computer Interaction (HCI), Computer-Supported Cooperative Work (CSCW), and social computing. My work focuses on designing and analyzing socio-technical systems that enhance collective competence, foster motivation, and integrate diverse perspectives into high-stakes decision-making contexts. I hold a multidisciplinary academic foundation that informs my approach to information science:

• Ph.D. in Information Science and Technology, Syracuse University (2019).
• M.S. in Library and Information Science, University of Illinois Urbana-Champaign (2012).
• B.A. in Political Science, University of Illinois Urbana-Champaign (2010).

Research Interests

My research agenda is broadly centered on two fundamental challenges in online collaboration:

• Augmented Expertise: How we can cultivate specialized expertise among distributed, non-expert users (such as citizen scientists) through adaptive scaffolding and hybrid intelligence systems.

• Algorithmic and Data Justice: How to ensure that data-driven and algorithmic systems in the public sector operate equitably and reflect community values rather than reinforcing systemic biases.

I employ an integrated methodology that bridges large-scale computational analysis of digital trace data with qualitative ethnography and community-engaged design.

My research has been supported by National Science Foundation (HCC), the Rockefeller Foundation, the Chan Zuckerberg Initiative, and the UW-Madison Office of the Vice Chancellor for Research and Graduate Education and appears in top HCI venues such as ACM Conference On Computer-Supported Cooperative Work And Social Computing, the Journal of the Association for Information Systems, and Computers in Human Behavior.

PhD Student Openings

I typically advise Ph.D. students interested in HCI, CSCW, responsible AI, and civic technology, particularly those excited about participatory methods, qualitative and mixed-methods research, and real-world public sector impact. However, availability varies by year. Prospective students are encouraged to review my advising philosophy and current projects before reaching out, and to clearly articulate how their interests align with ongoing work described above.

Updates

• [Jan 2026] Our paper ‘Seeing Like a Community: Public Perceptions of Data Use in Government’ has been accepted to CHI’26. Read the summary: How everyday people can spot risks that expert AI audits might miss.

• [Jan 2026] Our paper ‘Beyond Bias Detection: Non-Expert Auditors and Normative Reasoning in AI Oversight’ has been accepted to CSCW’26. Read the summary: How everyday people can spot risks that expert AI audits might miss.