Chao Dong

Professor
Shanghai AI Lab, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS)
chao.dong@siat.ac.cn

Chao Dong is currently a professor in Shenzhen Institute of Advanced Technology, Chinese Academy of Science, the leading scientist in Shanghai AI Laboratory. He received his Ph.D. degree from The Chinese University of Hong Kong, supervised by Prof. Xiaoou Tang and Prof. Chen Change Loy. In 2014, he first introduced deep learning method – SRCNN into the super-resolution field. This seminal work was chosen as one of the top ten “Most Popular Articles” of TPAMI in 2016. His team has won several championships in international challenges –NTIRE2018, PIRM2018, NTIRE2019, NTIRE2020 AIM2020 and NTIRE2022. He worked in SenseTime from 2016 to 2018, as the team leader of Super-Resolution Group. In 2021, he was chosen as one of the World’s Top 2% Scientists. In 2022, he was recognized as the AI 2000 Most Influential Scholar Honorable Mention in computer vision. As of March 2024, the citation count for Google Scholar has exceeded 33,222 times.His current research interest focuses on low-level vision problems, such as image/video super-resolution, denoising and enhancement.

董超，博士生导师，中国科学院深圳先进技术研究院研究员，上海人工智能实验室领军科学家，上海交通大学兼职博导。博士毕业于香港中文大学信息工程专业，导师为汤晓鸥教授和吕建勤教授。2014年，在欧洲计算机视觉大会（ECCV）上发表论文SRCNN，首次将深度学习引入图像超分辨领域。2017年至今，多次带队参加国际超分辨率比赛，共获得9项冠军。2016年-2018年就职于商汤科技，带领商汤超分团队开发了世界首款基于深度学习的数码变焦软件。2021年被斯坦福大学评选为世界前2%顶尖科学家。2022年被评为AI 2000人工智能全球最具影响力学者。截止到2024年3月，谷歌学术引用量超过3万3千次。主要研究方向包括图像视频超分辨率，去噪和画质增强等。

Research Interests: Image/Video Restoration, Super-Resolution