Stephanie Milani

I am an Assistant Professor / Faculty Fellow at NYU Courant. I work with Rajesh Ranganath and Sumit Chopra. In 2026, I will join Johns Hopkins University as an Assistant Professor in the Computer Science Department. My ultimate goal is to create practical AI agents that can learn from feedback to complement and augment human abilities. This involves studying, building, and improving techniques for reinforcement learning, foundation models, and human-centered AI.

I did my PhD in Machine Learning at Carnegie Mellon University, where I was advised by Fei Fang. I am a Rising Star in ML & Systems, a Future Leader in Responsible Data Science & AI, and a Rising Star in Data Science. During my PhD, I interned at Microsoft Research twice, once with Geoff Gordon and once with Katja Hofmann.

Selected Publications

For a full list, please see my Google Scholar.

LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning
Zhuorui Ye*, Stephanie Milani*, Geoffrey J Gordon, Fei Fang
ICLR, 2025

MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning
Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran
AAMAS, 2024

Explainable Reinforcement Learning: A Survey and Comparative Review
Stephanie Milani, Nicholay Topin, Manuela Veloso, Fei Fang
ACM Computing Surveys, 2024

BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks
Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander V Schulhoff, Brandon Houghton, Rohin Shah
NeurIPS D&B Track, 2023 (Oral)

Student Recruiting

The best way to work with me is to apply to the Computer Science Master's or PhD program at JHU. I'm particularly excited about highly-motivated students who enjoy thinking deeply and carefully about human-centered and real-world-inspired challenges of AI agents. An ideal applicant should have at least one core strength (especially software engineering, machine learning research, and algorithm design) and be eager to develop further as the PhD progresses. I unfortunately cannot respond to every email regarding admissions.