Academic Research

Julia Barnett, Hugo Flores García, and Bryan Pardo. “Exploring Musical Roots: Applying Audio Embeddings to Empower Influence Attribution for a Generative Music Model.” Under review at 2024 ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT). 2024. [PDF]

Julia Barnett. “The Ethical Implications of Generative Audio Models: A Systematic Literature Review.” Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society. 2023. [PDF]

Oral and poster presentation at 2023 AAAI/ACM Conference on AI, Ethics, and Society in Montreal, Quebec, Canada.

Julia Barnett, Margrét Vilborg Bjarnadóttir, David Anderson, and Chong Chen. 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). 

Julia Barnett 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 5th Annual AAAI/ACM Conference on AI, Ethics, and Society at University of Oxford, Oxford, England. (August 1-3 2022) [Video]

Julia Barnett*, Orsolya Vásárhelyi*, Emoke-Ágnes Horvát, and Stasa Milojevic. 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)

Julia Barnett, David Anderson, and Margrét Vilborg Bjarnadottir. Tell Me Why: Explaining Black-box Classification Algorithms Using Most Similar Counterfactuals. To submit to Informs Special Issue on The Human-Algorithm Connection.

Oral and Poster Presentation at the 5th Annual AAAI/ACM Conference on AI, Ethics, and Society at University of Oxford, Oxford, England. (August 1-3 2022) as part of the AIES student program.

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

Julia Barnett and Sivah Chandra. “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