Duygu Ceylan obtained her PhD in 2014 from EPFL. She holds a Bachelor and Master in Computer Science from Middle East Technical University and Bilkent University, respectively, and currently works as a senior researcher at Adobe Research.
Duygu’s research focuses on machine learning techniques and general computational methods to infer and analyze 3D information from images and videos. In her Ph.D. work at EPFL she focused on using computational shape understanding, specifically exploring symmetry priors, in the context of 3D reconstruction. This work is distinguished by a clear mathematical foundation to exploit semantic redundancy in structured environments, leading to robust algorithms for 3D scene modeling from image data. More recently, she explored machine learning methods for 3D scene understanding, geometry reconstruction, as well as human modeling. She proposed innovative neural network architectures for a variety of data modalities and inference tasks, thus significantly expanding the computational toolset for digital data analysis and modeling in computer graphics. Her work enables high-level understanding of visual and geometric data thus facilitating novel interaction schemes with applications ranging from image manipulation, human modeling, motion retargeting, to mechanism design.
Duygu has an impressive record of scientific achievements with a significant number of publications in the top venues of computer graphics, computer vision, and machine learning, such as ACM SIGGRAPH, CGF, CVPR, ECCV, and NeurIPS. In 2015 she received the Eurographics dissertation award. Her work is distinguished by a combination of solid mathematical foundation with high practical relevance. She has consistently broken new ground in her research and serves as a role model to others.
Eurographics is pleased to recognize Duygu Ceylan with the 2020 Young Researcher Award in recognition of her outstanding contributions to Computer Graphics in the area of 3D Scene reconstruction and understanding.