VNI Distinguished Lecture Series - AI for Optics and Optics for AI
Supporting the below United Nations Sustainable Development Goals:支持以下聯合國可持續發展目標：支持以下联合国可持续发展目标：
In this talk I will highlight recent work on the interconnection between AI techniques and (imaging) optics. In particular, I will describe AI methods for learning optical designs of camera optics, including some that boost the capabilities of conventional cameras with a form-factor suitable for mobile devices and small field-deployable sensors. I will also describe some on-going work on the reverse direction — optical designs that facilitate the computation for AI models while promising to reduce power consumption.
Wolfgang Heidrich is a Professor of Computer Science and Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), where he also served as the Director of the Visual Computing Center from 2014 to 2021, as well as a Visiting Professor at the University of Hong Kong (HKU). Prof. Heidrich joined KAUST in 2014, after 13 years as a faculty member at the University of British Columbia (UBC). He received his PhD in from the University of Erlangen in 1999, and then worked as a Research Associate in the Computer Graphics Group of the Max-Planck-Institute for Computer Science in Saarbrucken, Germany, before joining UBC in 2000. Prof. Heidrich’s research interests lie at the intersection of imaging, optics, computer vision, computer graphics, and inverse problems. His more recent interest is in computational imaging, focusing on hardware-software co-design of the next generation of imaging systems, with applications such as High-Dynamic Range imaging, compact computational cameras, hyperspectral cameras, to name just a few. Prof. Heidrich is a Fellow of the National Academy of Inventors, IEEE, Optica, AAIA, and Eurographics, and the recipient of a Humboldt Research Award as well as the ACM SIGGRAPH Computer Graphics Achievement Award.
Please register here: https://ust.az1.qualtrics.com/jfe/form/SV_1MuHQl16HF3oB82