I have worked as a machine learning research scientist for the last 13 years on various projects involving: computer vision, natural language processing, transfer learning, knowledge distillation, evolutionary algorithms and AI on embedded systems. I have a PhD in computer science with a focus on computer vision and scene understanding.

1. J. Davis et al., "Spatial Relationship-Driven Computer Vision Image Data Set Annotation," 2022 International Joint Conference on Neural Networks (IJCNN), 2022, pp. 1-8, doi: 10.1109/IJCNN55064.2022.9892975.
2. Davis, Jeremy, "Incorporating spatial relationship information in signal-to-text processing" (2022). Theses and Dissertations. 5397. https://scholarsjunction.msstate.edu/td/5397
3. Phillip J. Durst, David McInnis, Jeremy Davis, Christopher T. Goodin, A novel framework for verification and validation of simulations of autonomous robots, Simulation Modelling Practice and Theory, Volume 117, 2022, 102515, ISSN 1569-190X, https://doi.org/10.1016/j.simpat.2022.102515.
4. Davis, Jeremy E. et al. “Computational intelligence-based optimization of maximally stable extremal region segmentation for object detection.” Defense + Security (2017).
5. Davis, Jeremy E., Bednar, Amy E., Goodin, Christopher T. “Optimizing MSER Parameters Using the Particle Swarm Optimization Algorithm.” USACE Engineer Research and Development Center/Information Technology Laboratory Technical Report. Submitted November 2016. Report Date September 2019.
6. Guillermo A. Riveros, et al. “A Procedure for Predicting the Deterioration of Steel Hydraulic Structures to Enhance Their Maintenance, Management, and Rehabilitation,” (ERDC/ITL TR-14-1, Engineer Research and Development Center, June 2014).
7. J. Davis, J. MacLean and D. Dampier, "Methods of Information Hiding and Detection in File Systems," 2010 Fifth IEEE International Workshop on Systematic Approaches to Digital Forensic Engineering, 2010, pp. 66-69, doi: 10.1109/SADFE.2010.17.
8. Davis, JE, Maclean, JD, & Dornan, SJ. "Comparing Weight Generation Methods for Neural Networks Applied to the Road Pixel Identification Problem." Intelligent Engineering Systems through Artificial Neural Networks, Volume 20. Ed. Dagli, CH. ASME Press, 2010.
9. Brian J. Thomas, Jeremy E. Davis, Grant D. Patten, Paul A. Cleveland, Peter J. Gilbert, Matt T. Hogan, Shane P. Fry, John T. Foley, Taha Mzoughi, and David C. Banks. 2008. WebTOP: an X3D-based, web-delivered, interactive system for optics instruction. In Proceedings of the 13th international symposium on 3D web technology (Web3D '08). Association for Computing Machinery, New York, NY, USA, 31–34. https://doi.org/10.1145/1394209.1394219