Education:

Ph.D. 2014-2019, Robotics Institute, University of Michigan, Doctoral Thesis “Learning from the Field: Physically-based Deep Learning to Advance Robot Vision in Underwater Environments”

B.S.E. 2010-2014, Mechanical and Aerospace Engineering, Princeton University

Research Interests: ^top

Perception for underwater robots, light field imaging, and unsupervised learning.

Biography: ^top

Katherine Skinner received her Ph.D. from the Robotics Institute at the University of Michigan in 2019. Her research interests span robotics, machine learning, and computer vision, with a focus on enabling autonomy in dynamic, unstructured, or remote environments. She received a B.S.E. in Mechanical and Aerospace Engineering with a Certificate in Applications of Computing from Princeton University in 2014 and an M.S. in Robotics from the University of Michigan in 2016. She will begin September 2021.

Awards: ^top

She is a recipient of the NSF EAPSI Fellowship.

Publications: ^top

12. Alexandra Carlson, Katherine A. Skinner, Ram Vasudevan and Matthew Johnson-Roberson, “Sensor transfer: Learning optimal sensor effect image augmentation for sim-to-real domain adaptation.” In IEEE Robotics and Automation Letters (RA-L), 2019.

11. Junming Zhang, Katherine A. Skinner, Ram Vasudevan and Matthew Johnson-Roberson, “DispSegNet: Leveraging semantics for end-to-end learning of disparity estimation from stereo imagery.” In IEEE Robotics and Automation Letters (RA-L), 2019.

10. Katherine A. Skinner, Junming Zhang, Elizabeth Olson and Matthew Johnson-Roberson, “UWStereoNet: Unsupervised learning for depth estimation and color correction of underwater stereo imagery.” In IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.

9. Elizabeth Olson, Corina Barbalata, Katherine A. Skinner and Matthew Johnson-Roberson, “Synthetic data generation for deep learning of underwater disparity estimation.” In Proceedings of the IEEE/MTS OCEANS Conference and Exhibition, Charleston, USA, October 2018.

8. Alexandra Carlson*, Katherine A. Skinner*, Ram Vasudevan and Matthew Johnson-Roberson, “Modeling camera effects to improve visual learning from synthetic data.” In Proceedings of the European Conference on Computer Vision Workshop on Visual Learning and Embodied Agents in Simulated Environments (ECCV Workshops), Munich, Germany, 2018. *The authors contributed equally to this work.

7. Jie Li*, Katherine A. Skinner*, Ryan Eustice and Matthew Johnson-Roberson, “WaterGAN: Unsupervised generative network to enable real-time color correction of monocular underwater images.” In IEEE Robotics and Automation Letters (RA-L), 2017. *The authors contributed equally to this work.

6. Eduardo Iscar, Katherine A. Skinner and Matthew Johnson-Roberson, “Multi-view 3D reconstruction in underwater environments: evaluation and benchmark.” In Proceedings of the IEEE/MTS OCEANS Conference and Exhibition, Anchorage, USA, September 2017.

5. Katherine A. Skinner and Matthew Johnson-Roberson, “Underwater image dehazing with a light field camera.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop on Light Fields for Computer Vision (CVPR Workshops), Honolulu, USA, 2017.

4. Katherine A. Skinner, Eduardo Iscar Ruland and Matthew Johnson-Roberson, “Automatic color correction for 3D reconstruction of underwater scenes.” In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, 2017.

3. Katherine A. Skinner and Matthew Johnson-Roberson, “Towards real-time underwater 3D reconstruction with plenoptic cameras.” In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, 2016.

2. Katherine A. Skinner and Matthew Johnson-Roberson, “Detection and segmentation of underwater archaeological sites surveyed with stereo-vision platforms.” In Proceedings of the IEEE/MTS OCEANS Conference and Exhibition, Washington D.C., USA, October 2015.

1. Vittorio Bichucher, Jeffrey M. Walls, Paul Ozog, Katherine A. Skinner and Ryan M. Eustice, “Bathymetric factor graph SLAM with sparse point cloud alignment.” In Proceedings of the IEEE/MTS OCEANS Conference and Exhibition, Washington, D.C., USA, October 2015.