Matthew J. Hoffman

Matthew J. Hoffman

Journal Papers

  1. LaVigne, N.S., N. Holt, M.J. Hoffman, E.M. Cherry. 2017. Effects of model error on cardiac electrical wave state reconstruction using data assimilation. Chaos. Accepted.
  2. M.J. Hoffman and E. Hittinger. 2017. Inventory and transport of plastic debris in the Laurentian Great Lakes. Marine Pollution Bulletin. In Press.[Publisher Link][Preprint]
  3. Uzkent, B., M.J. Hoffman, and A. Vodacek. 2016. Integrating Hyperspectral Liklihoods in a Multi-dimensional Assignment Algorithm for Aerial Vehicle Tracking. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 99, 1-9, doi: 10.1109/JSTARS.2016.2560220.
  4. Hoffman, M.J. , N.S. LaVigne, S.T. Scorse, F.H. Fenton, and E.M. Cherry, 2016. Reconstructing 3D reentrant cardiac electrical wave dynamics using data assimilation, Chaos, 26, 013107, doi: 10.1063/1.4940238
  5. Uzkent, B., M.J. Hoffman, A. Vodacek, and B. Chen. 2014. Feature Matching with an Adaptive Optical Sensor in a Ground Target Tracking System, Sensors Journal IEEE, 99, doi: 10.1109/JSEN.2014.2346152.
  6. Urquhart, E, M.J. Hoffman, R. R. Murphy, and B.F. Zaitchik, 2013. Geospatial Interpolation of MODIS-Derived Salinity and Temperature in the Chesapeake Bay. Remote Sensing of the Environment, 135, 167-177.
  7. Greybush, S.J., E. Kalnay, M.J. Hoffman, R.J. Wilson. 2013. Identifying Martian atmospheric instabilities and their physical origins using bred vectors. Q. J. Roy. Meteor. Soc., 123 (672), 639-653, doi: 10.1002/qj.1990.
  8. Hoffman, M.J., T. Miyoshi, T. Haine, K. Ide, R. Murtugudde, and C.W. Brown. 2012. An advanced data assimilation system for the Chesapeake Bay. J. Atmos. and Oceanic Tech., 29, 1542-1557, doi: 10.1175/JTECH-D-11-00126.1.
  9. Urquhart, E, M.J. Hoffman, B.F. Zaitchik, S. Guikema, and E.F. Geiger. 2012. Remotely Sensed Estimates of Surface Salinity in the Chesapeake Bay. Remote Sensing of the Environment. 123, 522-531, doi: 10.1016/j.rse.2012.04.008.
  10. Greybush, S. J., R. J. Wilson, R. N. Hoffman, M.J. Hoffman, T. Miyoshi, K. Ide, T. McConnochie, and E. Kalnay. 2012. Ensemble Kalman Filter Data Assimilation of Thermal Emission Spectrometer Temperature Retrievals into a Mars GCM. J. Geophys. Res., 117, E11008, doi: 10.1029/2012JE004097.
  11. Hoffman, M.J., J. Eluszkeiwicz, D. Weisenstein, G. Uymin, and J.-L. Moncet. 2012. A Critical Assessment of Mars Atmospheric Temperature Retrievals from the Thermal Emission Spectrometer Measurements. Icarus, 220 (2), 1031-1039, doi: 10.1016/j/icarus.2012.06.039.
  12. Hoffman, M.J., S.J. Greybush, R.J. Wilson, G. Gyarmati, R.N. Hoffman, E. Kalnay, K. Ide, E. Kostelich, T. Miyoshi, I. Szunyogh. 2010. An ensemble Kalman filter data assimilation system for the Martian atmosphere: Implementation and simulation experiments. Icarus, 209, 470-481, doi: 10.1016/j.icarus.2010.03.034.
  13. Hoffman, M.J., E. Kalnay, J.A. Carton, and S.C. Yang. 2009. Use of breeding to detect and explain instabilities in the global ocean. Geophys. Res. Lett., 36, L12608, DOI: 10.1029/2009GL037729.
  14. Gibbons, K.S., M.J. Hoffman, and W.K. Wootters. 2004. Discrete phase space based on finite fields. Phys. Rev. A, 70, 062101, doi: 10.1103/PhysRevA.70.062101.

Peer-Reviewed Conference Papers

  1. Uzkent, B., A. Rangnekar, and M.J. Hoffman, 2017. Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood Maps. CVPR Workshop: Perception Beyond the Visible Spectrum, July 2017.
  2. Uzkent, B., M.J. Hoffman, and A. Vodacek, 2016. Real-time Vehicle Tracking in Aerial Video using Hyperspectral Features, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshop: Moving Cameras Meet Video Surveillance, June 2016. [Publisher Link]
  3. Uzkent, B., M.J. Hoffman, and A. Vodacek, 2015. Spectral Validation of Measurements in a Vehicle Tracking DDDAS, Procedia Computer Science, 51, pp. 2493-2502, 10.1016/j.procs.2015.05.358. [Publisher Link]
  4. Uzkent, B., M.J. Hoffman, and A. Vodacek, 2015. Efficient integration of spectral features for vehicle tracking utilizing an adaptive sensor. Proc. SPIE 9407, Video Surveillance and Transportation Imaging Applications 2015, 940707 (March 4, 2015), doi:10.1117/12.2082266. [Publisher Link]
  5. Uzkent, B., M.J. Hoffman, A. Vodacek, J. P. Kerekes, and B. Chen, 2013. Feature Matching and Adaptive Prediction Models in an Object Tracking DDDAS. Procedia Computer Science, 18, 1939-1948, doi: 10.1016/j.procs.2013.05.363. [PUblisher Link]
  6. Vodacek, A., J. P. Kerekes, and M.J. Hoffman. 2012. Adaptive optical sensing in an object tracking DDDAS. Procedia Computer Science, 9, 1159-1166, 10.1016/j.procs.2012.04.125.

Conference Papers

  1. Uzkent, B., M.J. Hoffman, A. Vodacek, and B. Chen., 2015. Background image understanding and adaptive imaging for vehicle tracking Proc. SPIE 9460, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XII, 94600F (May 19, 2015); doi: 10.1117/12.2177494. [Publisher Link]
  2. Uzkent, B., M.J. Hoffman, E. Cherry, and N. Cahill, 2014. 3-D MRI Cardiac Segmentation using Graph Cuts. Proc. IEEE Western New York Image Processing Workshop, pp. 47-51, November 2014, doi: 10.1109/WNYIPW.2014.6999484. [Publisher Link]