Matthew Hoffman Headshot

Matthew Hoffman

Associate Professor
School of Mathematical Sciences
College of Science

585-420-6288
Office Location
Office Mailing Address
2302 Gosnell Hall

Matthew Hoffman

Associate Professor
School of Mathematical Sciences
College of Science

Education

BA, Williams College; MS, Ph.D., University of Maryland

Bio

My research interests include oceanic and atmospheric dynamics; understanding the fate, transport, and impact of plastic pollution on freshwater systems; data assimilation; remote sensing; hyperspectral vehicle tracking; and cardiac electrical dynamics.

585-420-6288

Areas of Expertise

Currently Teaching

MATH-790
0 - 9 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
IMGS-699
0 Credits
This course is a cooperative education experience for graduate imaging science students.
MATH-791
0 Credits
Continuation of Thesis
IMGS-890
1 - 6 Credits
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
MATH-602
3 Credits
This course covers numerical techniques for the solution of nonlinear equations, interpolation, differentiation, integration, and matrix algebra.
MATH-606
1 Credits
The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics.

Latest News

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Journal Paper
Uzkent, Burak, Matthew J. Hoffman, and Anthony Vodacek. "Spectral Validation of Measurements in a Vehicle Tracking DDDAS." Procedia Computer Science 51. (2015): 2493—2502. Web.
Hoffman, Matthew J., et al. "Feature Matching with an Adaptive Optical Sensor in a Ground Target Tracking System." IEEE Sensors Journal 15. 1 (2015): 510--519. Print.
Hoffman, Matthew J., et al. "Integrating Hyperspectral Likelihoods in a Multi-dimensional Assignment Algorithm for Aerial Vehicle Tracking." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. (2015): --. Print.
Greybush, S. J., et al. "Ensemble Kalman Filter Data Assimilation of Thermal Emission Spectrometer Temperature Retrievals into a Mars GCM." Journal of Geophysical Research: Planets 117. E11 (2012) Web.
Hoffman, M. J., et al. "An Advanced Data Assimilation System for the Chesapeake Bay: Performance Evaluation." J. Atmos. Oceanic Technol. 29. (2012): 1542-1557. Print.
Greybush, Steven J., et al. "Identifying Martian atmospheric instabilitiesand their physical origins using bred vectors." Quarterly Journal of the Royal Meteorological Society. (2012) Print.
Urquhart, E., et al. "Remotely Sensed Estimates of Surface Salinity in the Chesapeake Bay." Remote Sensing of the Environment 23. (2012): 522-531. Print.
Hoffman, M. J., et al. "Assessment of Mars Atmospheric Temperature Retrievals from the Thermal Emission Spectrometer Radiances." Icarus 220. 2 (2012): 1031-1039. Print.
Published Conference Proceedings
Uzkent, Burak, Matthew J. Hoffman, and Anthony Vodacek. "Efficient integration of spectral features for vehicle tracking utilizing an adaptive sensor." Proceedings of the SPIE Conference on Video Surveillance and Transportation Imaging Applications. Ed. Robert Loce and Eli Saber. San Francisco, CA: n.p., 2015. Web.
Uzkent, Burak, et al. "Background image understanding and adaptive imaging for vehicle tracking." Proceedings of the SPIE Conference on Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XII. Ed. Daniel J. Henry, et al. Baltimore, MD: n.p., 2015. Web.
Hoffman, Matthew J. "Spectral Validation of Measurements in a Vehicle Tracking DDDAS." Proceedings of the Procedia Computer Science. , Reykjavik: , 2015. Print.
Hoffman, Matthew J. "Background Image Understanding and Adaptive Imaging for Vehicle Tracking." Proceedings of the SPIE Defense + Security. Baltimore, Maryland: SPIE, 2015. Print.
Hoffman, Matthew J. "Efficient Integration of Spectral Features for Vehicle Tracking Utilizing an Adaptive Sensor." Proceedings of the IS&T/SPIE Electronic Imaging 2015. San Francisco, California: SPIE, 2015. Print.
Uzkent, Burak, et al. "Feature Matching and Adaptive Prediction Models in an Object Tracking DDDAS." Proceedings of the Procedia Computer Science. n.p., 2013. Print.
Invited Keynote/Presentation
Hoffman, Matthew J. "Ground Target Tracking Utilizing DDDAS Based Control of an Adaptive Optical Sensor." IEEE Geoscience and Remote Sensing Joint Chapter Meeting. IEEE Geoscience and Remote Sensing Joint Chapter. Rochester, NY. 31 Mar. 2015. Lecture.