Priyanka Nanayakkara


Photo by Gabrielle Ferra

priyankan [at]

Hi! I’m a PhD student in a dual program in computer science and communication at Northwestern University. My advisor is Professor Jessica Hullman. I’m interested in studying 1) how algorithms can be more effectively implemented and 2) their downstream consequences. Lately, I have been thinking about the social challenges arising around the U.S. Census Bureau’s adoption of differential privacy.

I also co-organize HCI+D’s PhD Book Club. We read books that help us think critically about technology and media.

During Spring 2022, I am a visiting PhD student at Columbia University working under the guidance of Professors Rachel Cummings, Elissa Redmiles, and Gabriel Kaptchuk on explaining differential privacy to end users.


Visualizing Privacy–Utility Trade-Offs in Differentially Private Data Releases
Priyanka Nanayakkara, Johes Bater, Xi He, Jessica Hullman, Jennie Rogers
Forthcoming in PETS 2022 | PDF | demo

Unpacking the expressed consequences of AI research in broader impact statements
Priyanka Nanayakkara, Jessica Hullman, Nicholas Diakopoulos
AIES 2021 | PDF | blog post

Workshop Papers and Non-Archival Publications

Anticipatory ethics and the role of uncertainty
Priyanka Nanayakkara, Nicholas Diakopoulos, Jessica Hullman
Navigating the Broader Impacts of AI Research Workshop at NeurIPS 2020 | PDF

Toward better communication of uncertainty in science journalism
Priyanka Nanayakkara and Jessica Hullman
Computation + Journalism 2020 | PDF

Public Writing

States Are Suing the Census Bureau Over Its Attempts to Make Data More Private. Slate, August 2021. (with Jessica Hullman)

Here’s how AI researchers are thinking about the societal impacts of AI. Technically Social, May 2021.

Teaching (as a TA)

CS 333: Interactive Information Visualization, Northwestern University, Fall 2021


Advanced Cognitive Science Fellowship (2020-2021), Northwestern University

Data Science Fellowship (2019-2020), Northwestern Institute on Complex Systems (NICO)