Meet the Fellow: Lucius Bynum
This entry is a part of our Meet the Fellow blog series, which introduces and highlights incoming Faculty Fellows at CDS.
Meet CDS Faculty Fellow Lucius Bynum, who is starting as Faculty Fellow this fall after recently completing his PhD at CDS in 2025.
Bynum’s research focuses on causal machine learning, which he describes as integrating causal inference (CI) tools into machine learning (ML) and accelerating CI applications using ML.
“I’m interested in Causal ML because it ultimately touches on core challenges across causal inference, machine learning, and artificial intelligence, from making robust, non-spurious predictions to choosing optimal actions and treatments,” said Bynum. “My recent work draws on fundamental connections between CI and ML, for example, reframing causal inference as meta-learning, or combining language models and structural causal models to fundamentally improve average as well as heterogeneous treatment effect estimation.”
Bynum’s past research has also tackled inequality-aware decision making, leveraged counterfactual reasoning to improve ML model explainability and reduce pre-existing disparities, and reimagined how causal modeling formalisms are used in AI problems involving demographic data.
“I am particularly excited to continue developing new collaborations that bridge causal inference and machine learning work at CDS, such as my ongoing work with CDS Professor Kyunghyun Cho. I can’t think of a better place to be doing this than in the vibrant research community at NYU.”
Bynum emphasized his commitment to understanding the systems we build: “In both my research and teaching, I am passionate about better understanding the systems we build, improving their capabilities in real-world contexts, and enabling positive impacts on the people downstream of predictions.”
To view all of our current faculty fellows, please visit the CDS Faculty Fellows page on our website.
By Stephen Thomas
