About me
I am an Assistant Professor in the School of Computing and Augmented Intelligence at Arizona State University. My research interests are in probabilistic reasoning and learning (tractable probabilistic models, graphical models, knowledge compilation) and trustworthy AI/ML (robustness, fairness, explainability, and more).
Before joining ASU, I received my PhD from the Computer Science department at UCLA, advised by Guy Van den Broeck.
I am currently looking for students at all levels. Please email me if you are interested.
News
- August 2023: In Fall 2023, I will be visiting the Simons Institute for the Theory of Computing at UC Berkeley.
- December 2022: We presented our new and improved tutorial Probabilistic Circuits: Representations, Learning, and Reasoning at NeurIPS 2022! Watch it here.
- November 2022: Our paper Certifying Fairness of Probabilistic Circuits was accepted to AAAI 2023!
- November 2022: I was selected for the AAAI 2023 New Faculty Highlights Program.
- August 2022: I started as an assistant professor at ASU. <!– * June 2022: I defended my PhD thesis!
- January 2022: Our paper Solving Marginal MAP Exactly by Probabilistic Circuit Transformations was accepted to AISTATS 2022! –>
Recent publications
A Probabilistic Approach to Fairness under Label Bias
Saurav Anchlia and YooJung Choi.
In the 6th Workshop on Tractable Probabilistic Modeling (TPM), 2023.
PDF BibTex
Certifying Fairness of Probabilistic Circuits
Nikil Roashan Selvam, Guy Van den Broeck, and YooJung Choi.
In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023.
PDF BibTex Code
Solving Marginal MAP Exactly by Probabilistic Circuit Transformations
YooJung Choi, Tal Friedman, and Guy Van den Broeck.
In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022.
PDF BibTex
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference
Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, and Guy Van den Broeck.
In Advances in Neural Information Processing Systems 35 (NeurIPS), 2021.
Oral presentation (acceptance rate 55/9122 = 0.6%)
PDF BibTex Code