Julia B Barnett

JuliaBarnett[at]u.northwestern.edu

@JuliaBarnettEdu

LinkedIn

she / her

PhD Candidate at Northwestern

Hello! I'm Julia Barnett and I'm a PhD student in Technology and Social Behavior, which is a dual PhD program in computer science and communications at Northwestern University. My advisor is Nicholas Diakopoulos, and right now we are researching different areas in the ethical AI space, most recently the ability to anticipate societal impacts of algorithms through crowdsourcing. Currently I am working with Ágnes Horvát investigating the intersectional penalty of gender and ethnic diversity of scientific teams on success in scientific publications.

My research interests lie in algorithmic ethics and transparency, ethical AI, NLP applications in social contexts, and the intersection of machine learning and music.

I completed a Master's Degree in Data Science at the Barcelona Graduate School of Economics in 2019, and I got my Bachelor's Degree in Business Analytics, International Business, and Marketing from Villanova University in 2018. Before my PhD I finished up a two year stint as a Senior Data Analyst at The Washington Post.

Academic Research


Barnett J, Bjarnadóttir M, Anderson D, and Chen C. Understanding Gender Biases and Differences in Web-Based Reviews of Sanctioned Physicians Through a Machine Learning Approach: Mixed Methods Study. JMIR Form Res. 2022 Sep 8;6(9):e34902. doi: 10.2196/34902. PMID: 36074543. [Open Access Article]


Oral presentation at the Informs Annual Meeting in Indianapolis, IN, USA. (October 16-29, 2022).


Barnett, Julia, and Nicholas Diakopoulos. "Crowdsourcing Impacts: Exploring the Utility of Crowds for Anticipating Societal Impacts of Algorithmic Decision Making." Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society. 2022. [PDF]


Oral and poster presentation at Conference on AI, Ethics, and Society at University of Oxford, Oxford, England. (August 1-3 2022) [Video]

Vásárhelyi O, Barnett J, Horvát E-Á, Milojevic S. Intersectional Inequalities in the Impact of Online Visibility on Citations.

Best Student Paper – Contributed talk at International Conference on the Science of Science and Innovation (ICSSI) at the National Academy of Sciences, Washington D.C., USA. (June 7-9 2022)


Poster presentation at 8th International Conference on Computational Social Science (IC2S2) at University of Chicago, Chicago, IL, USA. (July 19-22 2022)


Oral Presentation at Debugging (In)equality in Data Science Workshop at the London School of Economics, London, England. (May 6 2022)


Barnett J, Anderson D, Bjarnadottir M. Tell Me Why: Explaining Black-box Classification Algorithms Using Most Similar Counterfactuals. To submit to Informs Special Issue on The Human-Algorithm Connection. (Dec. 2022)


Barnett J, Chandra S. “Watchdog or Lapdog? A Critique on the Role of Journalism in the United States and Singapore.” Published: Ahead and Behind: Singapore in the World, Pagesetters Services Pte Ltd. Editors: Pang Eng Fong, Arnoud de Meyer. (2018)

Fellowships and Academic Awards

Best Student Paper (2022) – International Conference on the Science of Science and Innovation (ICSSI)

Data Science Fellowship (2021-2022), Northwestern Institute on Complex Systems (NICO)

Professional Experience

Short Term Consultant, The World Bank, Washington, D.C., USA 04/2022 - 06/2022

Create visualization dashboards for the the curriculum, instruction, and learning team at The World Bank’s Global Education Practice division.

Senior Data Analyst, The Washington Post, Washington, D.C., USA 09/2019 - 09/2021

Work with every team at the Washington Post (the newsroom, marketing, finance, product, etc.) on a variety of data science and analytics projects. Personal areas of ownership are subscription retention, forecasting, elections, and the homepage.

Junior Data Scientist, Accenture Analytics, Barcelona, Spain 04/2019 - 07/2019

Organized Accenture's annual Hackathon (a Machine Learning Competition on survival analysis for melanoma patients); additionally analyzed health and fitness data to bring methodologies/technologies together to create value for clients