Linda Shapiro, Professor of Computer Science and Engineering, Professor of Electrical and Computer Engineering, and Adjunct Professor of Biomedical and Informatics and Medical Education, earned a bachelor's degree in mathematics from the University of Illinois in 1970 and master's and Ph.D degrees in computer science from the University of Iowa in 1972 and 1974, respectively. She was a faculty member in Computer Science at Kansas State University from 1974 to 1978 and at Virginia Polytechnic Institute and State University from 1979 to 1984. She then spent two years as Director of Intelligent Systems at Machine Vision International in Ann Arbor, Michigan. She joined the University of Washington Electrical Engineering (now ECE) Department Department in 1986 and the Computer Science and Engineering Department in 1990. Professor Shapiro's research is in computer vision with related interests in image and multimedia database systems, artificial intelligence (search, reasoning, knowledge representation, learning), and applications in medicine and robotics. She has worked heavily in knowledge-based 3D object recognition and has contributed to both the theory of object matching and to the development of experimental machine vision systems. Her current work includes robot vision, cancer biopsy analysis, brain image analysis, and semantic segmentation. Professor Shapiro was the …
Xiaodan Liang’s research is focused on developing interpretable and explainable neural-symbolic reasoning techniques for boosting vision and cross-modal understanding tasks (open-world detection/segmentation, robotic interaction, and digital human) which will provide trustworthy and robust systems for real-world applications. She published over 80 top-tier papers about cross-modal understanding, human analysis, and human-robot interaction tasks. Her Google Scholar citation is over 19000. Xiaodan Liang served as area chair of ICCV 2019, CVPR 2020, NeurIPS 2021-2023, WACV 2021, Tutorial Chair (Organization committee) of CVPR 2021, and Ombud Committee of CVPR 2023. She has been awarded the ACM China and CCF Best Doctoral Dissertation Award, the Alibaba DAMO Academy Young Fellow (Top 10 under 35 in China), and the ACL 2019 Best Demo paper nomination. She is named one of the young innovators 30 under 30 by Forbes (China). She and her collaborators have also published the largest human parsing dataset to advance the research on human understanding, and successfully organized four workshops and challenges on CVPR 2017, CVPR 2018, CVPR 2019, CVPR 2020, CVPR 2023. She also organized ICML 2019 and ICLR 2021 workshops respectively.