Xun Huang

My name is Xun Huang (pronounced as /shuun hwang/). I am a Senior Research Scientist at Adobe and also an Adjunct Faculty at CMU. My recent research focuses on real-time, interactive, and autoregressive video/world models. I lead the interactive video world model research at Adobe.

I was a researcher at NVIDIA prior to joining Adobe. I developed one of the first text-to-image demo with multimodal control (GauGAN2), coauthored papers that serve as the basis of NVIDIA's text-to-image and text-to-3D foundation models and shipped them into production.

I obtained my PhD in Computer Science from Cornell in 2020, advised by Professor Serge Belongie. During my PhD, I invented Adaptive Instance Normalization (AdaIN) and was the first to demonstrate its effectiveness in generative neural networks. AdaIN became a foundational component of StyleGAN and played a key role in the first working diffusion model. Variants of AdaIN are now used in nearly all state-of-the-art diffusion models. My PhD research was supported by Adobe Research Fellowship (2019), Snap Research Fellowship (2019), and NVIDIA Graduate Fellowship (2018).