Meet the Team
David Allemang
Senior R&D Engineer
Kitware North Carolina
Carrboro, NC
B.S. in Computer Science
UNC Charlotte
B.S. in Mathematics
UNC Charlotte
David Allemang is an R&D engineer on Kitware’s Medical Computing Team. He specializes in building visualizations to better understand high-dimensional structures, combining his expertise in computer science and mathematics. His work at Kitware focuses on developing open source tools that make a tangible impact in the medical domain.
David contributes to platforms like 3D Slicer and SlicerSALT, and leverages these tools to build custom software for Kitware’s commercial customers. He has expertise in CT and X-ray image data, statistical shape modeling, and workflows for surgical planning and navigation. His notable open source projects include SlicerHeart, SlicerCMF, and NousNav. He also applies his software engineering skills to optimize interactive data processing workflows, leveraging GPGPU and SIMD computation for enhanced performance.
In addition to his projects, David mentors new hires, conducts technical interviews, and supports Kitware’s commitment to fostering growth and excellence.
David holds dual bachelor’s degrees in computer science and mathematics from the University of North Carolina at Charlotte. During his studies, he concentrated on high-performance computing and computer graphics, as well as modern and abstract linear algebra. He is currently pursuing his master’s degree in computer science from the University of North Carolina at Chapel Hill, supported by Kitware’s Tuition Reimbursement program.
Publications
- M. Gillot, F. Miranda, B. Baquero, A. Ruellas, M. Gurgel, N. Al Turkestani, L. Anchling, N. Hutin, E. Biggs, M. Yatabe, B. Paniagua, J. Fillion‐Robin, D. Allemang, J. Bianchi, L. Cevidanes, and J. Prieto, "Automatic landmark identification in cone‐beam computed tomography," Orthodontics & Craniofacial Research, vol. 26, no. 4, pp. 560-567, Nov. 2023. [URL]
- H. Nam, M. Flynn, A. Lasso, C. Herz, P. Sabin, Y. Wang, A. Cianciulli, C. Vigil, J. Huang, J. Vicory, B. Paniagua, D. Allemang, D. Goldberg, M. Nuri, M. Cohen, G. Fichtinger, and M. Jolley, "Modeling of the Tricuspid Valve and Right Ventricle in Hypoplastic Left Heart Syndrome With a Fontan Circulation," Circulation: Cardiovascular Imaging, vol. 16, no. 3, Mar. 2023. [URL]
- M. Hawrylycz et al., "A guide to the BRAIN Initiative Cell Census Network data ecosystem," PLOS Biology, vol. 21, no. 6, pp. e3002133, Jun. 2023. [URL]
- J. Vicory, Y. Han, J. Prieto, D. Allemang, M. Leclercq, C. Bowley, H. Scheirich, J. Fillion-Robin, S. Pizer, J. Fishbaugh, G. Gerig, M. Styner, and B. Paniagua, "SlicerSALT: From Medical Images to Quantitative Insights of Anatomy," in Shape in Medical Imaging. Springer Nature Switzerland, 2023, pp. 201-210. [URL]
- É. Léger, S. Horvath, J. Fillion-Robin, D. Allemang, S. Gerber, P. Juvekar, E. Torio, T. Kapur, S. Pieper, S. Pujol, R. Bardsley, S. Frisken, and A. Golby, "NousNav: A low-cost neuronavigation system for deployment in lower-resource settings," International Journal of Computer Assisted Radiology and Surgery, vol. 17, no. 9, pp. 1745-1750, May 2022. [URL]
- J. Vicory, C. Herz, D. Allemang, H. Nam, A. Cianciulli, C. Vigil, Y. Han, A. Lasso, M. Jolley, and B. Paniagua, "Statistical Shape Analysis of the Tricuspid Valve in Hypoplastic Left Heart Syndrome," in Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. Springer International Publishing, 2022, pp. 132-140. [URL]
- J. Vicory, C. Herz, Y. Han, D. Allemang, M. Flynn, A. Cianciulli, H. Nam, P. Sabin, A. Lasso, M. Jolley, and B. Paniagua, "Skeletal Model-Based Analysis of the Tricuspid Valve in Hypoplastic Left Heart Syndrome," in Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers. Springer Nature Switzerland, 2022, pp. 258-268. [URL]
- J. Vicory, D. Allemang, D. Zukic, J. Prothero, M. McCormick, and B. Paniagua, "An open-source solution for shape modeling of objects of challenging topologies," in Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2021. [URL]
