Nan Liu

I am a MSCS student at University of Illinois at Urbana-Champaign. And I am currently interning at Adobe Research. Previously, I graduated from University of Michigan, Ann Arbor with a bachelor's degree in Computer Science in 2021.

My current research is focused on applications of generative models (i.e., energy-based models, diffusion models/score-based models). I am particularly interested in leveraging compositionality within generative models.

Email / Github / Twitter / Google Scholar

Selected Publications

(* indicates equal contribution)

	Compositional Visual Generation with Composable Diffusion Models Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, Joshua B. Tenenbaum ECCV 2022* [Website] [Paper] [Code] [Colab] [Demo] [MIT News]
	Learning to Compose Visual Relations Nan Liu, Shuang Li, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba NeurIPS 2021 (Spotlight)* / NeurIPS 2021 Workshop on Controllable Generative Modeling (Outstanding Paper Award) [Website] [Paper] [Code] [MIT News]
	FIBER: Fill-in-the-Blanks as a Challenging Video Understanding Evaluation Framework Santiago Castro, Ruoyao Wang, Pingxuan Huang, Ian Stewart, Oana Ignat, Nan Liu, Jonathan Stroud, Rada Mihalcea ACL 2022 [Paper] [Code]

Teaching

CS 543: Computer Vision (Fall 2022)

CS 441: Applied Machine Learning (Fall 2021, Spring 2022)

Template from Jon Barron, and design from Joyce Yang.