I'm currently a Ph.D. candidate in Information Science at Cornell University, based in NYC at Cornell Tech. I'm very lucky to be advised primarily by Nicola Dell and Deborah Estrin, with additional mentorship from Thomas Ristenpart, Karen E.C. Levy, Mary L. Gray, and many other collaborators. Currently, I am supported by a Microsoft Research PhD Fellowship.
tl;dr: I'm interested in (a) understanding how the data-driven turn across the sciences is restructuring our infrastructures for care, creating novel risks to safety, privacy, health and well-being, and (b) designing alternative systems that reap the benefits of computation---scale, standardization---while mitigating its harms.
contact me: Email is best. You can reach me at et397 at cornell dot edu. I also tweet sometimes.
Longer version: Increasingly, our efforts to improve people's lives involve gathering large amounts of data on their trauma or pain, analyzing it using machine learning methods increasingly less and less subject to human oversight, and then using that analysis to make design and policy decisions. I want us to be able to do this rigorously and with attention to core human values like privacy, agency, and equity. To me, this is a combination of evolution in our data analysis techniques (e.g., privacy-preserving machine learning), our approaches to gathering and curating datasets (e.g., informed consent and data stewardship), and our technology design frameworks (e.g., participatory design). In my PhD thus far, I have worked specifically on computer security and privacy for survivors of intimate partner violence, worker-centered design for home care aides, and workplace surveillance and mental health. I have also spent time investigating how the technology industry can work with communities towards health equity.
Methodologically, I build on techniques from human-computer interaction (HCI) and computational social science (CSS). I first investigate novel sources of harm, using large-scale analyses of social datasets and high-touch design research with impacted communities. Where appropriate, I mount interventions employing novel social and technical systems, and work with communities to sustain them. Through rigorous empirical knowledge production, I work concurrently towards theoretical and methodological interventions that can help address these harms upstream, at the level of technology design, law, and policy.
My home field is HCI and social computing, and I maintain active footprints in computer security, medicine and public health, and privacy. Together with my amazing collaborators, students and mentors, I have earned best paper awards at CHI, CSCW, and USENIX Security. Our work has additionally been published in JAMA, a top-tier medical journal, and appeared at highly selective privacy conferences, including the Privacy Law Scholars Conference and the Reidenberg Northeast Privacy Scholars Workshop. In addition to scholarly accolades, my work has achieved real-world impact: I am part of the team building the Clinic to End Tech Abuse (CETA), where my work has helped provide survivors of tech-enabled intimate partner surveillance with volunteer security and privacy support. CETA has served hundreds of survivors in the New York City area since 2018, and earned accolades from the New York City Mayor's Office to End Gender-Based Violence.
Before this, I earned a B.A. from Princeton University in Ecology and Evolutionary Biology (EEB), a field-leading department in computational approaches to understanding the biological and social worlds. I focused on the epidemiology and control of infectious disease epidemics, and my undergraduate thesis earned the department's top prize in mathematical modeling. I also earned an M.S. from Cornell Tech in Health Tech, where I added graduate-level education in machine learning and HCI to my toolkit. In previous lives I made radio, print and multimedia journalism and ran early-stage product development at a consumer health tech startup. I've also worked as a healthcare consultant in the U.S. and taught software engineering.