Kellie Corona, Ph.D.

Data Informatics Analyst

Computer Vision

Kitware New York
Clifton Park, NY

Ph.D. in Physics
University of North Carolina at Chapel Hill

M.S. in Physics
University of North Carolina at Chapel Hill

B.S. in Physics and Mathematics
Texas State University in San Marcos

Kellie Corona

Kellie Corona, Ph.D. is a data informatics analyst working remotely on Kitware’s Computer Vision Team. She is responsible for annotation quality and efficiency across Kitware’s computer vision projects. She works with internal, third-party, and crowdsourced annotation processes to design workflows that optimize efficiency and quality for project-specific data labeling.

As part of the IARPA Deep Intermodal Video Analytics (DIVA) program, Kellie was responsible for the experimental design and implementation of scripted scenarios to ensure the realism and program requirements for the 100-actor multi-camera data collection. She also helps lead the effort for annotating the resulting data using internal annotators, external annotation companies, and crowdsourcing platforms. 

Kellie works on developing full-pipeline annotation data management and tooling pipelines for crowdsourced annotations. She implements metrics for performance, reliability, and quality control in annotations. As a part of this work, she develops and implements new techniques and tools into the annotation workflow to improve efficiency, performance, and management. She also builds curricula for training the Kitware annotation team, providing this training and professional guidance during the annotation process.

Prior to joining Kitware, Kellie worked at the Computer Integrated Systems for Microscopy and Manipulation Center where she focused on the development of instrumentation, analysis techniques, and visualization tools for a wide range of biological and materials projects. Her research aimed to develop a novel approach for high-resolution, high-speed fluorescence imaging of mechanically deformed samples. This involved the development of analysis packages and visualization tools for synchronous examination of two-dimensional strain mapping from fluorescence images and direct mechanical measurements from atomic force spectroscopy.

Kellie received her Ph.D. and master’s degree in physics from the University of North Carolina at Chapel Hill. She received her bachelor’s degree in physics and mathematics from Texas State University in San Marcos. 


  1. D. Davila, D. Du, B. Lewis, C. Funk, J. Van Pelt, R. Collins, K. Corona, M. Brown, S. McCloskey, A. Hoogs, and B. Clipp, "MEVID: Multi-view Extended Videos with Identities for Video Person Re-Identification," in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023. [URL]
  2. B. Ravichandran, R. Collins, K. Fieldhouse, K. Corona, and A. Hoogs, "From Leaderboard To Operations: DIVA Transition Experiences," in 2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), 2022. [URL]
  3. K. Corona, K. Osterdahl, R. Collins, and A. Hoogs, "MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection," in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2021. [URL]
  4. R. Collins, K. Osterdahl, A. Shringi, K. Corona, R. Meth, and A. Hoogs, "Data, Algorithms, and Framework for Automated Analytics of Surveillance Camera Networks," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2018. [URL]

Bibliography generated 2023-02-13-10:30:04 (5868)