Ryan Steed - Homepage

Ryan Steed (he/him)

I am a Ph.D. candidate at Carnegie Mellon's Heinz College of Information Systems & Public Policy and Machine Learning Department, advised by Alessandro Acquisti. I evaluate ethics and privacy in algorithmic systems to help improve tech governance. Previously, I studied Computational Economics at the George Washington University.

I am currently on the job market! I plan to graduate spring 2025.



Research

Working Papers

News

I'm presenting a poster at TPDP & giving a talk at the OpenDP Community Meeting DP Beyond Algorithms workshop this week — stop by and see our work on census privacy and DP adoption.

08/18/2024

Our work on the adoption of privacy-preserving analytics received the George Duncan Award for Best Second Research Paper at Heinz College.

05/10/2024

I'll be presenting our work on privacy-preserving analytics at the NBER Conference on Data Privacy Protection and the Conduct of Applied Research May 16-17.

05/10/2024

I'm presenting our work on the landscape of AI auditing at SaTML, where we received a Distinguished Paper award!

04/10/2024

I'll be presenting our work-in-progress on privacy-preserving analytics adoption Sep. 11-12 at PEPR.

07/31/2023

Our work-in-progress on privacy-preserving analytics adoption will be discussed at PLSC '23.

05/15/2023

I'll be presenting our work-in-progress case study on privacy risks of public statistics to residents of subsidized housing at the NBER Conference on Data Privacy Protection and the Conduct of Applied Research May 4-5.

04/17/2023

I'll be speaking about our Science paper at Hot Topics in the Science of Security.

04/03/2023

I'm giving a talk on our Science paper at the Boston Data Privacy Group this Friday, 10/14/2022.

10/11/2022

We wrote a blog post for Brookings about our study on bias in unsupervised computer vision and its policy implications.

09/26/2022

Our paper on statistical uncertainty, differential privacy and census-guided funding was published in Science. We'll be presenting it at EAAMO 2022 October 6-9 - tune in!

08/25/2022

I'm presenting some work-in-progress at the Theory and Practice of Differential Privacy Workshop @ ICML 2022 - come stop by our poster!

06/14/2022

I'm (virtually) attending ACL 2022 to present our paper on bias transfer in pre-trained language models.

05/17/2022

Received the Suresh Konda Ph.D. First Research Paper Award from Heinz for our paper on the disparate impacts of uncertainty (and privacy) on census-guided grants.

05/11/2022

Awarded a Meta PhD Research Fellowship.

02/02/2022

Awarded a TCS Presidential Fellowship.

08/24/2021

Excited to be joining Oracle to work on fairness & bias as a research intern this summer.

05/17/2021

I'm (virtually) attending FAccT 2021 and presenting our paper on unsupervised bias in computer vision - DM me on Twitter or in the conference platform if you want to chat!

03/05/2021

Contributed to an awesome transparency tool for the Cook County Assessor's Office. Check out our presentation at the SolveForGood DataFest!

09/14/2020

Our paper was accepted to the Participatory Approaches to Machine Learning workshop @ ICML! We propose and test an alternative way to elicit & incorporate stakeholder preferences in ML systems.

07/10/2020

Excited to join Carnegie Mellon's Heinz College of Information Systems & Public Policy to start my PhD this fall. Thank you to all the wonderful people who helped me along the way!

05/15/2020

Very proud to have (virtually) defended my undergraduate thesis in front of a wonderful committee of GWU faculty.

04/28/2020

I'll be hanging out at AIES-2020! Say hi if you're around - I'm excited to learn about new work in the field.

02/06/2020