I am a Ph.D. candidate at the University of Michigan School of Information and Department of Computer Science & Engineering, advised by Kentaro Toyama. To ethically and effectively create social media and AI that give users the agency to shape their online interactions, my research develops and evaluates systems from the lens of consent. Consent—the affirmative permission one grants to another to access information or take action—is necessary for system creators to responsibly leverage users’ data or enable interactions they find comfortable. Yet, computer science as a field has lacked a thorough understanding of what consent is, and what that means for system design.

More specifically, my claim is that consent is a better framework for considering a range of privacy, permissions, and related issues, because traditional permission models tend to be system and outcome-centric, whereas consent is inherently user-centric and process-focused. Permission models tend to be based on engineers' or lawyers' conception of privacy, where ease of programming or fidelity to some policy is the primary goal. But, the forms of information exchange that people consent to are dependent on identities and relationships, and privacy settings do not come close to representing such complexity. A consent focus would not be satisfied until users can adjust who they interact with, clearly, easily, flexibly, and at any time. During my PhD, I have:

• theorized what affirmative consent is—drawing from feminist literature, which stresses a culture of care and impacts on marginalized groups, I proposed a theoretical framework of affirmative consent to reimagine social platforms (CHI 2021)
• built consentful systems and interfaces—e.g., Moa, a platform that enables sensitive information-sharing among people with less power, by letting users flexibly and precisely carve out an audience per post/comment through "consent boundaries"; consent-granting mechanisms regarding tech companies' data collection and algorithmic inferences (CHI 2023, CHI 2024)

Ulitmately, my goal is to reimagine forms of human-computer interactions where users are thoroughly respected, to support more effective and ethical computing. I identify myself as a Human-Computer Interaction, Social Computing, and Privacy researcher.

My research has been recognized with a Meta Research PhD Fellowship (selected on my fourth try), University of Michigan Barbour Scholarship, EECS Rising Star, and two honorable mentions. I am on the academic job market for 2024-2025.