Lucius EJ Bynum
PhD Candidate. NYU Center for Data Science.
Microsoft Research PhD Fellow.
I am 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.
In my research, I use causal inference and statistics to better understand bias and inequality in AI systems, machine learning, and algorithmic decision making. This work includes developing tools for inequality-aware decision making and more wholistic algorithmic fairness, leveraging counterfactual reasoning to improve model explainability and reduce pre-existing disparities, and reimagining how we use causal modeling formalisms to reason about social categories like race and gender.
I am also passionate about teaching via public outreach and making educational material in these areas.
My research is generously supported by the Microsoft Research PhD Fellowship.
news
Jan 25, 2024 | New preprint release: A New Paradigm for Counterfactual Reasoning in Fairness and Recourse. |
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Dec 16, 2023 | Oral presentation at the NeurIPS Workshop on Algorithmic Fairness Through the Lens of Time (NeurIPS AFT2023) on Backtracking Counterfactual Fairness. Thanks to the organizers for a great workshop! |
Aug 15, 2023 | Gave a presentation at the KAIST Data Intelligence Lab in Daejeon, Korea as part of the NYU-KAIST Inclusive AI Workshop. Thanks to everyone at KAIST and especially Professor Stephen Whang and his lab for being such wonderful hosts! |
Jul 29, 2023 | Poster presentations at the ICML 2023 Workshop on Counterfactuals in Minds and Machines on Counterfactuals for the Future as well as Causal Dependence Plots. |
Jun 26, 2023 | New AAAI’23 publication: Counterfactuals for the Future. |