Gao Wei, Ph.D., assistant professor/Associate researcher/doctoral supervisor, School of Information Engineering, Peking University, SENIOR member of IEEE, Shenzhen overseas high-level talent. He received his PhD in computer science from City University of Hong Kong, and was a visiting scholar at UCLA, as well as a postdoctoral fellow at City University of Hong Kong and Nanyang Technological University in Singapore. He worked as an image signal processor ASIC chip design engineer at OmniVision Technologies, a CMOS image sensor manufacturer. His research interests include: (1) Multimedia coding and processing: point cloud and video coding, deep learning intelligent coding; 3D point cloud processing and analysis, as well as immersive and 3D visual media perception quality evaluation, visual attention mechanism and saliency segmentation, restoration and enhancement, 3D target detection, etc. (2) Deep learning and artificial intelligence: Machine learning/deep learning and optimization theory and applications, interpretable deep neural network theory, deep learning algorithm lightweight/structure search and software/hardware acceleration in artificial intelligence. In recent years, more than 60 papers have been published on high-level international IEEE Transactions journals (such as IEEE TIP, TCSVT, TMM, TCYB, TIM, TII, etc.) and high-level international conferences (such as CVPR, AAAI, ACM MM, DCC, etc.). Applied for or authorized more than 40 US/Chinese /PCT patents, and actively participated in the standard proposal of multimedia and artificial intelligence technology.

Awarded the ICME 2021 Multimedia Rising Star Award (one of only four winners in the world) for his research in 3D immersive media, He was awarded the CCF-Tencent Rhinoceros Bird Excellent Patent Award in 2021, the CCF-Tencent Rhinoceros Bird Fund (international Open Competitive Fund, scientific Research Fund global selection rate of 12%) in 2020 and 2019, and the First prize of Excellent Paper of Guangdong Computer Society in 2019 (the first author's paper). Invited to serve as the Associate Editor of four internationally important SCI journals in the field of multimedia computing and machine learning. JCR journals include Signal Processing (Elsevier), Neural Processing Letters (Springer), etc. He is also a member of the Image, Video and Multimedia Technology Committee (APSIPA IVM TC) of the Asia Pacific Association for Signal and Information Processing. Organized QoEIM Workshop for Interactive Media Visual Quality Evaluation and Perception Modeling at ICME 2021. National Natural Science Foundation of China, guangdong Province and Shenzhen project evaluation expert. As a reviewer of several international top journals IEEE TIP, TCSVT, TMM, TNNLS, TCYB, etc., as well as important international academic conferences CVPR, ECCV, IJCAI, etc., and a member of the program committee and organizer of several international academic conferences. The research group has close r&d cooperation with Tencent Multimedia Lab, Tencent Turing Lab and Huawei Technologies Co., LTD. In cooperation with Pengcheng Laboratory, the research group is building and maintaining open source algorithm libraries for point cloud technology and visual information compression, including OpenPointCloud, OpenCompression and OpenVision.

The research group is committed to enhancing the viewing experience and industrial application of immersive and 3D visual media, and promoting the development of emerging and future multimedia and visual information processing technologies. The School of Information Engineering welcomes outstanding undergraduate and master students to apply or apply for the master's and doctoral programs, and welcome to apply for postdoctoral or visiting positions in the research group to engage in the research and exploration of hot and cutting-edge topics related to multimedia computing and artificial intelligence. https://gaowei262.github.io/.

As the project leader, he has presided over or is currently presiding over more than 10 important national and provincial scientific research projects with sufficient scientific research funds.