Jun Xing (邢骏)

junxnui@gmail.com (+86)15996380819
WeChat: junxfriend

My work focuses on a hybrid research of Graphics and Human Computer Interaction (HCI). I have broad interest in machine/deep learning for text, image and video analysis and generation, VR/AR for content creation, and UI/UX design. In particular, I am interested in analyzing the repetitions in human-centered activities, such as painting and writing, and providing online “intelligent” suggestions, via a natural interface, to reduce manual labor while improving quality and performance.

I have my PhD study in the Department of Computer Science, University of Hong Kong, under the supervision of Dr. Li-Yi Wei, and I got my Bachelor's Degree in Electronic Engineering and Information Science in 2012, from University of Science and Technology of China (USTC), where my research was about Super-resolution of single image.

Find my CV and research statement.

Work Experience

  • Adobe, Procedural Imaging Group Intern, San Jose, July 11, 2016 - Sep. 30, 2016

  • Autodesk Research, UI Graphics Research Intern, Toronto, Jan. 11, 2016 - April 30, 2016

  • Microsoft Research Asia, Graphics Research Intern, Beijing, Dec. 08, 2014 - April 30, 2015


Energy Brushes: Interactive Tools for Illustrating Stylized Elemental Dynamics

Jun Xing, Rubaiat Habib Kazi, Tovi Grossman, Li-Yi Wei, Jos Stam and George Fitzmaurice

UIST 2016

[paper] [Youtube] [presentation/slides]


We present a new animation framework and interactive system that enables artists to design elemental dynamics by sketching the underlying forces.


Autocomplete Hand-drawn Animations

Jun Xing, Li-Yi Wei, Takaaki Shiratori and Koji Yatani

SIGGRAPH Asia 2015

[paper] [Youtube] [Wired] [Fastcompany]


We present an interactive drawing system that helps users produce animation more easily and in a better quality while preserving manual drawing practices.


Autocomplete Painting Repetitions

Jun Xing, Hsiang-Ting Chen and Li-Yi Wei

SIGGRAPH Asia 2014

[paper] [Youtube]


We present an interactive digital painting system that autocompletes tedious repetitions while preserving nuanced variations and maintaining natural flows.

PhD Thesis

Autocomplete Hand-drawn Sketches and Animations

Jun Xing

University of Hong Kong



This thesis is basically a concatenation of my first three projects.