Lucius is a PhD Candidate at the NYU Center for Data Science advised by Julia Stoyanovich as part of the Center for Responsible AI and working closely with Joshua Loftus at the London School of Economics. His research focuses on the intersection between responsible data science, causal inference, and inequality—looking at statistical aspects of inequality problems, the modeling of social categories, and techniques that can aid in the responsible and transparent use and analysis of data. His research is generously supported by the Microsoft Research PhD Fellowship.
Selected publications
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice
Andrew Bell, Lucius Bynum, Nazarii Drushchak, Tetiana Herasymova, Lucas Rosenblatt, and Julia Stoyanovich
Proceedings of the Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2023
@article{bell2023possibility,title={The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice},author={Bell, Andrew and Bynum, Lucius and Drushchak, Nazarii and Herasymova, Tetiana and Rosenblatt, Lucas and Stoyanovich, Julia},journal={Proceedings of the Conference on Fairness, Accountability, and Transparency (ACM FAccT)},year={2023},keywords={fairness, theory, impossibility}}
Counterfactuals for the Future
Lucius E. J. Bynum, Joshua R. Loftus, and Julia Stoyanovich
@article{bynum2022interactive,author={Bynum, Lucius E.J. and Khan, Falaah Arif and Konopatska, Oleksandra and Loftus, Joshua R. and Stoyanovich, Julia},title={An Interactive Introduction to Causal Inference},journal={VISxAI: Workshop on Visualization for AI Explainability},year={2022},site={https://r-ai.co/ci-playground},publisher={IEEE},keywords={workshop,education,playground},}
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice
Andrew Bell, Lucius Bynum, Nazarii Drushchak, Tetiana Zakharchenko, Lucas Rosenblatt, and Julia Stoyanovich
In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023, Chicago, IL, USA, June 12-15, 2023 2023
@article{AllAboard,author={{Arif Khan}, Falaah and Bynum, Lucius and Hurst, Amy and Rosenblatt, Lucas and Shanbhogue, Meghana and Sloane, Mona and Stoyanovich, Julia},title={{All Aboard! Making AI Education Accessible}},journal={Center for Responsible AI, New York University},keywords={panel,education,weareai},year={2023},}
Disaggregated Interventions to Reduce Inequality
Lucius Bynum, Joshua R. Loftus, and Julia Stoyanovich
In EAAMO 2021: ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, Virtual Event, USA, October 5 - 9, 2021 2021
@inproceedings{bynum2023counterfactuals,author={Bynum, Lucius E. J. and Loftus, Joshua R. and Stoyanovich, Julia},title={Counterfactuals for the Future},url={https://ojs.aaai.org/index.php/AAAI/article/view/26655},doi={10.1609/aaai.v37i12.26655},number={12},booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},year={2023},pages={14144-14152},keywords={journal,fairness,causal,counterfactuals},}
An Interactive Introduction to Causal InferenceVISxAI: Workshop on Visualization for AI Explainability 2022
