Keith Fieldhouse

Director of Cyber-Physical Systems

Company Leadership
Computer Vision

Kitware New York
Clifton Park, NY

10 Years Service at Kitware

M.A. in Military History
Norwich University

B.S. in Computer Science
Rochester Institute of Technology

Keith Fieldhouse

Keith Fieldhouse is the director of cyber-physical systems on Kitware’s Computer Vision Team located in Clifton Park, New York. He focuses on projects that involve deploying and evaluating cutting-edge AI systems in the field. He also has an interest in the ethical, legal, and societal implications of AI, authoring blog articles and overseeing government-funded projects in these areas.

Most recently, Keith has served as the chief engineer for the sensing portion of the DARPA Urban Reconnaissance through Supervised Autonomy (URSA) program which focused on military threat assessment in urban environments using multiple stationary and mobile cameras.  He filled the same role on the DARPA Squad X Core Technologies program to develop technologies for infantry squad-embedded ground based robots to enable them to identify distant, fleeting threats. 

Keith has conducted operations for numerous large-scale experiments, including Trident Spectre and Joint Interagency Field Experimentation (JIFX). He has experience leading Kitware efforts for the Air Force Research Lab (AFRL), the Office of Naval Research (ONR), and the Army Research Lab (ARL), among others. 

As a former co-op student himself, Keith is very involved with Kitware’s software development co-op and internship program, frequently traveling to technical universities in the region to conduct interviews and present Kitware to students.  

Prior to joining Kitware, Keith worked at Simmetrix, Inc, where he was the lead and principal architect of a Python-based rapid development environment for Simulation-Based Design. Before his time at Simmetrix, Keith held a position at Adobe Systems, where he pioneered Adobe’s early online commerce activities and joined the Consumer Systems Group. This group was dedicated to bringing Adobe technology to non-traditional consumer computing devices, such as set-top boxes. The Consumer Systems Group was spun out by Adobe as PictureIQ, Inc., where Keith served as the head of engineering. In this role, he architected and developed award-winning server technology for the then-nascent online photo industry. Keith also previously worked at IBM, the Digital Equipment Corporation, and as an independent software developer writing medical diagnostic software. 

Keith received his bachelor’s degree in computer science from Rochester Institute of Technology. He received his master’s degree in military history from Norwich University, where he studied Cold War-era weapons system development.


  1. C. Funk, D. Depauw, K. Fieldhouse, and E. Blasch, "Fog-Assisted Autoencoder for Enhanced Multi-INT Targeting," in Proceedings of the National Security Sensor and Data Fusion Committee (NSSDF), 2023.
  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. B. RichardWebster, B. Hu, K. Fieldhouse, and A. Hoogs, "Doppelganger Saliency: Towards More Ethical Person Re-Identification," in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022. [URL]
  4. M. Brown, K. Fieldhouse, A. Romlein, D. Davila, E. Borovikov, A. Lynch, and A. Hoogs, "Person Tracking, Re-identification, and Threat Detection by Autonomous Unmanned Systems within Complex Urban Environments," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2021.
  5. M. Brown, K. Fieldhouse, E. Swears, P. Tunison, A. Romlein, and A. Hoogs, "Multi-Modal Detection Fusion on a Mobile UGV for Wide-Area, Long-Range Surveillance," in 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 2019. [URL]
  6. M. Brown, K. Fieldhouse, E. Swears, P. Tunison, A. Romlein, and A. Hoogs, "Multi-Modal Detection Fusion on Mobile UGV for Squad-Level Threat Alerting," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2018.
  7. S. Han, A. Fafard, J. Kerekes, M. Gartley, E. Ientilucci, A. Savakis, C. Law, J. Parhan, M. Turek, K. Fieldhouse, and T. Rovito, "Efficient generation of image chips for training deep learning algorithms," in SPIE Defense + Security, 2017. [URL]
  8. M. Dawkins, L. Sherrill, K. Fieldhouse, A. Hoogs, B. Richards, D. Zhang, L. Prasad, K. Williams, N. Lauffenburger, and G. Wang, "An open-source platform for underwater image and video analytics," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2017. Winner, Best Paper Honorable Mention. [URL]
  9. K. Fieldhouse, A. Hoogs, and E. Swears, "Linking Unmanned Systems, Visible and IR Video, Computer Vision, and Humans Together for Real-Time, Squad-Level, Battlefield Situational Awareness: THreat Reconnaissance and Exploitation from Audio-video Target eXtraction (THREAT X)," in AUVSI XPONENTIAL Conference, 2017.
  10. C. Law, J. Parham, M. Dawkins, P. Tunison, D. Stoup, R. Blue, K. Fieldhouse, M. Turek, A. Hoogs, S. Han, A. Farafard, J. Kerekes, E. Lentilucci, M. Gartley, T. Savakis, T. Rovito, S. Thomas, and C. Stansifer, "Deep learning for object detection and object-based change detection in satellite imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
  11. K. Fieldhouse, A. Hoogs, and E. Swears, "Fusing Visible and Infrared (IR) Video on Mobile Robots, UAVs and Warfighters for Real-Time, Squad-Level Situational Awareness," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
  12. M. Turek, A. Basharat, K. Fieldhouse, P. Tunison, D. Stoup, C. Atkins, and A. Hoogs, "Real-time, full-frame wide area motion imagery analytics," in Proceedings of the MSS National Symposium on Passive Sensors, 2015.
  13. A. Hoogs, A. Perera, R. Collins, A. Basharat, K. Fieldhouse, C. Atkins, L. Sherrill, B. Boeckel, R. Blue, M. Woehlke, C. Greco, Z. Sun, E. Swears, N. Cuntoor, J. Luck, B. Drew, D. Hanson, D. Rowley, J. Kopaz, T. Rude, D. Keefe, A. Srivastava, S. Khanwalkar, A. Kumar, C. Chen, J. Aggarwal, L. Davis, Y. Yacoob, A. Jain, D. Liu, S. Chang, B. Song, A. Roy-Chowdhury, K. Sullivan, J. Tesic, S. Chandrasekaran, B. Manjunath, X. Wang, Q. Ji, K. Reddy, J. Liu, M. Shah, K. Chang, T. Chen, and M. Desai, "An end-to-end system for content-based video retrieval using behavior, actions, and appearance with interactive query refinement," in Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2015. [URL]
  14. K. Fieldhouse, M. Leotta, A. Basharat, R. Blue, D. Stoup, C. Atkins, L. Sherrill, B. Boeckel, P. Tunison, J. Becker, M. Dawkins, M. Woehlke, R. Collins, M. Turek, and A. Hoogs, "KWIVER: An open source cross-platform video exploitation framework," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2014. [URL]
  15. A. Basharat, M. Turek, Y. Xu, C. Atkins, D. Stoup, K. Fieldhouse, P. Tunison, and A. Hoogs, "Real-time multi-target tracking at 210 megapixels/second in Wide Area Motion Imagery," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2014. [URL]

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