Linda Shapiro, Professor of Computer Science and Engineering, Professor of Electrical 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 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 facial expression recognition, cancer biopsy analysis, 3D face and head analysis and reconstruction, and object segmentation in videos.
Professor Shapiro is a member of the editorial boards of Computer Vision and Image Understanding and of Pattern Recognition. She was the editor-in-chief of Computer Vision, Graphics, and Image Processing for 10 years. She was the 1993-95 chair of the IEEE Computer Society Technical Committee on Pattern Analysis and Machine Intelligence, conference chair of the 1986 IEEE Conference on Computer Vision and Pattern Recognition and co-program chairman of the 1994 conference. She was the co-chair of the Biomedical and Multimedia Applications Track of the International Conference on Pattern Recognition in 2002 and co-chair of the IEEE Conference on Computer Vision and Pattern Recognition in 2008. She has also co-authored a textbook on data structures, a two-volume graduate text on computer and robot vision, and an undergraduate computer vision text.
Awards & Honors
Pattern Recognition Society Best Paper Awards 1989, 1995
IEEE Fellow, 1996
IAPR Fellow, 2000
- Wenjun Wu, Sachin Mehta, Shima Nofallah, Stevan Knezevich, Caitlin J. May, Oliver H. Chang, Joann G. Elmore and Linda G. Shapiro, "Scale-Aware Transformers for Diagnosing Melanocytic Lesions", IEEE Access, 2021.
- E. Mercan, S. Mehta, J. Bartlett, L. G. Shapiro, D. L. Weaver, J. G. Elmore, "Assessment of Machine Learning of Breast Pathology Structures for Automated Differentiation of Breast Cancer and High-Risk Proliferation Lesisions." JAMA Network Open, Vol. 2, No. 3, 2019.
- S. Mehta, M. Rastegari, L. Shapiro, H. Hajishirzi, "ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network," CVPR 2019.
- S. Mehta, E. Mercan, J. Bartlett, D. Weaver, J. G. Elmore, L. Shapiro, "Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images," MICCAI 2018.
- B. Gecer, S. Aksoy, E. Mercan, L. G. Shapiro, D. L. Weaver, J. G. ELmore, "Detection and classification of cancer in whole slide breast histopathology images using deep convolutional networks," Pattern Recognition Volumn 84, 2018, pp. 345-356.
- S. Mehta, E. Mercan, J. Bartlett, D. Weaver, J. Elmore, L. Shapiro, "Learning to Segment Breast Biopsy Whole Slide Images," WACV 2018.
- E. Mercan, S. Mehta, J. Barlett, D. Weaver, J. G. Elmore, L. G. Shapiro, "Automated Diagnosis of Breast Cancer and Pre-invasive Lesions on Digital Whole Slide Images," ICPRAM 2018, Portugal.
- Karl Jablonowski, BIME (Ph.D. expected Spring '19)
- Deepali Aneja, CSE (Ph.D. expected Summer '19)
- Sachin Mehta, ECE (Ph.D. expected '20)
- Bindita Chaudhuri, CSE (Ph.D. expected '21)
- Sean Yang, ECE (Ph.D. expected '21)
- Shima Nofallah, ECE (Ph.D. expected '22)
- Meredith Wu, BIME (Ph.D. expected '22)
- Nicholas Neuchterlein, CSE (Ph.D. expected '22)
- Beibin Li, CSE (Ph.D. expected '22)
- Jie Gao, Stat (Ph.D. expected '22)