Academic Research

Patrick O’Reilly, Julia Barnett, Hugo Flores García, Annie Chu, Nathan Pruyne, Prem Seetharaman, and Bryan Pardo. “The Rhythm In Anything: Audio-Prompted Drums Generation with Masked Language Modeling.” Proceedings of the 2025 26th International Society for Music Information Retrieval (ISMIR) Conference. 2025.

Julia Barnett, Kimon Kieslich, Natali Helberger, and Nicholas Diakopoulos. “Envisioning Stakeholder-Action Pairs to Mitigate Negative Impacts of AI: A Participatory Approach to Inform Policy Making.” Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency (FAccT). 2025. [PDF].

Oral presentation at the 2025 ACM Conference on Fairness, Accountability, and Transparency (FAccT) in Athens, Greece. 

(June 23-26). 

Annie Chu, Patrick O’Reilly, Julia Barnett, Bryan Pardo. Text2FX: "Harnessing CLAP Embeddings for Text-Guided Audio Effects." To be published in the proceedings of the 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 2025. [PDF].

Julia Barnett, Hugo Flores García, and Bryan Pardo. “Exploring Musical Roots: Applying Audio Embeddings to Empower Influence Attribution for a Generative Music Model.” Proceedings of the 25th International Society for Music Information Retrieval (ISMIR) Conference. 2024. [PDF]

Oral and poster presentation at the 25th International Society for Music Information Retrieval (ISMIR) Conference in San Francisco, CA, USA. (November 10-14, 2024).

Julia Barnett, Kimon Kieslich, and Nicholas Diakopoulos. "Simulating Policy Impacts: Developing a Generative Scenario Writing Method to Evaluate the Perceived Effects of Regulation." Proceedings of the 2024 AAAI/ACM Conference on AI, Ethics, and Society. [PDF]

Poster presentation at the 2024 AAAI/ACM Conference on AI, Ethics, and Society in San Jose, CA, USA. (October 21-23, 2024).

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 the 2023 AAAI/ACM Conference on AI, Ethics, and Society in Montréal, Québec, 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

Research Grant (2024-25) – National Artificial Intelligence Research Resource (NAIRR) Pilot

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