Jingwan joined Adobe Research in 2014. She is currently leading a team of research scientists and engineers with the vision to disrupt visual content creation with big data and generative AI. Her research interests include generative image modeling (GANs, etc.), computational photography, digital human and data-driven artistic content creation. She has over 30 issued patents and over 40 publications in top vision, graphics and machine learning conferences. Some of them attracted lots of public attentions for example, Scribbler, VoCo, StyLit, FaceStyle, Playful Palette. Jingwan served as a program committee member for Siggraph, Siggraph Asia and Eurographics.
Jingwan is passionate about making real-world impacts with her research. She shipped RealBrush into Adobe Photoshop Sketch in 2016 and to Behance ios in 2018. RealBrush is a generic data-driven brush synthesis model that can be used to simulate natural media brushes, including but not limited to Soft Pastel, Thick Acrylic and Ink Brush. She contributed to the shipping of face stylization feature to Character Animator in 2018, Smooth Skin and Colorize Photo AI features to Photoshop Element in 2019. She and her team members are the main algorithm contributors to smart portrait, skin smoothing, makeup transfer, colorization and neural stylization neural filters in Photoshop in 2020.