Professor Kristin Dana joined the Department of Electrical and Computer Engineering in 1999. Her research interests include computer vision, robotics, AI, computational photography, and machine learning. She has recently received a $3 million, five-year National Science Foundation Research Traineeship (NSF NRT) grant for her project, “SOCRATES: Socially Cognizant Robotics for a Technology Enhanced Society.”
By integrating technology with social and behavioral sciences, SOCRATES aims to develop and implement an innovative, transformative approach to STEM graduate education training.
Visit the SOCRATES website here: https://robotics.rutgers.edu/
B.S., Electrical Engineering and Computer Science, Cooper Union and New York University, New York, NY, 1990
- Robotic Bridge Assessment, Project Contributor for 2014 Charles Pankow Award - American Society of Civil Engineering Innovation Award
- Rutgers Electrical and Computer Engineering Departmental Service Award 2011
- National Science Foundation CAREER Award 2001
- Sarnoff Technical Achievement Award 1994, for the development of a unique and practical algorithm to align infrared and visible images
- NYU Computer Science and Engineering Award 1990
- General Electric "Faculty of the Future" Fellowship 1990
- Computer Vision
- Pattern Recognition
- Machine Learning
- Convex Optimization
- Novel Cameras
- Camera Networks
- Computer Graphics
- Computational Photography
1. Akiva, Peri, Benjamin Planche, Aditi Roy, Kristin Dana, Peter Oudemans, and Michael Mars. "AI on the Bog: Monitoring and Evaluating Cranberry Crop Risk." In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 2493-2502. 2021.
2. Matthew Purri, Kristin Dana, “Teaching Cameras to Feel: Estimating Tactile Physical Properties of Surfaces From Images”, European Conference on Computer Vision ECCV 2020
3. Wengrowski, Eric, and Kristin Dana. “Light Field Messaging With Deep Photographic Steganography”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019.
4. Xue, Jia, Hang Zhang, and Kristin Dana. “Deep Texture Manifold for Ground Terrain Recognition.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 558-567. 2018
5. Zhang, Hang, Kristin Dana, Jianping Shi, Zhongyue Zhang, Xiaogang Wang, Ambrish Tyagi, and Amit Agrawal. “Context encoding for semantic segmentation.” In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018