The Asia Graphics Association (AG) is proud to announce the winner of the Young Researcher Award (2020). This award is to recognize young researchers early on in their career (not longer than 6 years after obtaining the PhD degree), who have made a recently, notable contribution to the field of computer graphics and interactive techniques, in an Asiagraphics country. The winner of this award was selected by the award jury chaired by Prof. Ming Lin (UMD College Park) and Prof. Leif Kobbelt (RWTH Aachen).

The 2020 AG’s Young Researcher Award was presented to Dr. Lin Gao, who obtained his B.S. at Mathematics from Sichuan University and his PhD degree at Computer Science from Tsinghua University. Since 2014, he joined the Institute of Computing Technology, Chinese Academy of Sciences and after two years he was promoted to an associate professor with his excellent research records. The main scientific focus of Dr. Gao’s work lies in the field of geometry processing with an emphasis on intelligent shape analysis and modeling. He is also the pioneer on intelligent geometry processing with deep learning.

Dr. Gao’s scientific work compels by its profound mathematical analysis and its deep insight into the geometry structure of the shape collections. A serials of works with excellent research records are proposed to enforce the intelligent of the geometry processing. For instance, his ACM TOG 2016 paper presents an efficient and flexible deformation representation (RIMD) which could handle shape collections with large scale deformations. This work plays a fundamental role in the analysis and synthesis of the deformed shape collections. Next, he further developed a novel shape representation (called ACAP) which shares the same advantages with RIMD feature and especially it is suitable for the graph convolution operations. Based on these approaches from deformation representation to associated deep convolution neural nets, a fully automatic deformation transfer method for the mesh models without correspondence is proposed in the SIGGRAPH ASIA 2018. This work is without any user efforts and could transfer the deformations between two unpaired shape sets. At SIGGRAPH Asia 2019, he proposed a deep generative neural network (SDM-NET) to produce structured deformable meshes.  The superiority of SDM-NET in generating meshes is with quite fine geometry details and flexible structures. These breakthrough research results demonstrate Dr. Gao’s leading position in the field of deep geometry learning and are also leading to the future research.

Besides on the intelligent geometry processing, Dr. Gao has also made contributions in other visual media processing including the cartoon, facial images generation et al. Recently, He and his students developed the intelligent face drawing board "DeepFaceDrawing" inspired by the geometry learning ideas of "local to global". Users without any painting experience can use this system to draw high-quality facial images as they imagined. Once the system was released, it caused a sensation at home and abroad. At present, users in more than 120 countries have used the service. This research work is also accepted by SIGGRAPH 2020 and selected into the SIGGRAPH technique papers preview trailer.

Dr. Gao has a prolific publication record: He has published more than 30 papers, including five ACM SIGGRAPH\TOG papers and seven IEEE TVCG papers. Dr. Gao is also very activity and make contributions to the community, he servers the program committee member for the SGP, PG, AAAI and the CVM, he also serves as the reviewers for several Computer Graphics conferences and journals including SIGGRAPH (ASIA), IEEE TVCG, Computer Graphics Forum etc.