By David Murphy
CEMSE Professor Wolfgang Heidrich will receive the Association for Computing Machinery’s Special Interest Group on Computer Graphics and Interactive Technique’s (ACM SIGGRAPH) Computer Graphics Achievement Award this August. The ACM SIGGRAPH is a global nonprofit organization that advances computer graphics and interactive technologies.
Together with the Steven Anson Coons Award, the Computer Graphics Achievement Award represents the most prestigious recognition in the research area of computer graphics. The award is given to an individual for outstanding achievement in computer graphics and interactive techniques; it includes a prize of $2,000.
According to the ACM SIGGRAPH, Professor Heidrich will be honored for “fundamental contributions to the development and analysis of computational imaging and display systems.”
Heidrich will be recognized at the 50th annual conference of the ACM SIGGRAPH, SIGGRAPH 2023. The leading meeting in computer graphics will be held in Los Angeles, U.S., from August 6-10.
Felix Heide, a former Ph.D. student in Heidrich’s group at the University of British Colombia, Canada, and now an assistant professor of computer science at Princeton University, U.S., will also receive a major award at SIGGRAPH 2023, the Significant New Researcher Award.
“I am deeply honored to receive the award and see it as a validation of our approach of co-designing the hardware and software components of imaging and display systems, which we pioneered in my group and the KAUST Visual Computing Center (VCC),” he noted of his award win.
Heidrich is a member of the KAUST VCC; he served as the Center’s director for eight years between 2014 and 2021. His work at KAUST focuses on the area of computational imaging and displays. In this emerging research area within visual computing, researchers use computers and software to push the boundaries of photography.
Heidrich and his colleagues in the Computational Imaging Group develop novel sensing and display technologies by combining computer graphics, machine vision, imaging, inverse methods, optics and perception.
At present, the group is focused on end-to-end learned imaging systems, increasing the complexity of the optical design space and expanding the methodology to fully automate the design of complex optical systems instead of individual components.