Matthew J. Hoffman
Professor  ·  School of Mathematics & Statistics  ·  Rochester Institute of Technology

Publications

Journal Papers
  1. Rochman, C. M., K. Bucci, D. Langenfeld, R. McNamee, C. Veneruzzo, G. A. Covernton, G. H. Y. Gao, M. Ghosh, R. N. Cable, L. Hermabessiere, R. Lazcano, M. J. Paterson, M. D. Rennie, R. C. Rooney, P. Helm, M. B. Duhaime, T. Hoellein, K. M. Jeffries, M. J. Hoffman, D. M. Orihel, and J. F. Provencher (2024). Informing the Exposure Landscape: The Fate of Microplastics in a Large Pelagic In-Lake Mesocosm Experiment. Environmental Science & Technology Article ASAP. DOI: 10.1021/acs.est.3c08990 [Publisher Link]
  2. Zhu, X., M. J. Hoffman, and C. M. Rochman (2024). A City-Wide Emissions Inventory of Plastic Pollution. Environmental Science & Technology, 58 (7), 3375–3385. DOI: 10.1021/acs.est.3c04348 [Publisher Link]
  3. McIlwraith, H.K., M. Dias, D. M. Orihel, M. D. Rennie, A. L. Harrison, M. J. Hoffman, J. F. Provencher, and C. M. Rochman (2024). A Multicompartment Assessment of Microplastic Contamination in Semi-remote Boreal Lakes. Environ Toxicol Chem. doi:10.1002/etc.5832 [Publisher Link]
  4. Marcotte, C. D., M. J. Hoffman, F. H. Fenton, E. M. Cherry (2023). Reconstructing cardiac electrical excitations from optical mapping recordings. Chaos, 33 (9). doi:10.1063/5.0156314 [Publisher Link]
  5. Lobyrev, F. and M. J. Hoffman (2023). A method for estimating fish density through the catches of gill nets. Fisheries Management and Ecology. [Publisher Link]
  6. Wang, J., K. Bucci, P. Helm, T. Hoellein, M. J. Hoffman, R. Rooney, & C. Rochman (2022). Runoff and discharge pathways of microplastics into freshwater ecosystems: A systematic review and meta-analysis. FACETS, 7, 1473–1492. doi:10.1139/facets-2022-0140 [Publisher Link]
  7. Mendez, M. J., M. J. Hoffman, E. M. Cherry, C. A. Lemmon, and S. H. Weinberg (2022). A data-assimilation approach to predict population dynamics during epithelial-mesenchymal transition. Biophysical Journal, 121 (16). [Publisher Link]
  8. Daily, J., A. C. Tyler, and M.J. Hoffman (2022). Modeling three-dimensional transport of and impacts of biofouling in Lake Erie and Lake Ontario. J. Great Lakes Res. 45 (5). [Publisher Link]
  9. Daily, J., V. Onink, C.E. Jongedijk, C. Laufkotter, and M.J. Hoffman (2022). Incorporating terrain specific beaching within a lagrangian transport plastics model for Lake Erie. Microplastics and Nanoplastics, 1(1), 19. [Publisher Link]
  10. Onink, V, C. Jongedijk, M.J. Hoffman, E. Van Sebille, and C. Laufkotter (2021). Global simulations of marine plastic transport show plastic trapping in coastal zones. Environmental Research Letters, 16(6), 064053. [Publisher Link]
  11. Marcotte, C. D., Fenton, F. H., Hoffman, M. J., & Cherry, E. M. (2021). Robust data assimilation with noise: Applications to cardiac dynamics. Chaos, 31(1), 013118. doi:10.1063/5.0033539 [Publisher Link]
  12. M.J. Hoffman and E.M. Cherry (2020). Sensitivity of a data-assimilation system for reconstructing three-dimensional cardiac electrical dynamics. Phil. Trans. R. Soc. A. 378: 20190388. [Publisher Link]
  13. Rangnekar, A., N. Mokashi, E.J. Ientilucci, C. Kanan and M.J. Hoffman. 2020. AeroRIT: A New Scene for Hyperspectral Image Analysis. IEEE Transactions on Geoscience and Remote Sensing. [Publisher Link]
  14. Daily, J. and M.J. Hoffman. 2020. Modeling the three-dimensional transport and distribution of multiple microplastic polymer types in Lake Erie. Marine Pollution Bulletin, 154. doi:10.1016/j.marpolbul.2020.111024 [Publisher Link]
  15. Mendez, M.J., M.J. Hoffman, E.M. Cherry, C.A. Lemmon, and S.H. Weinberg. 2020. Cell Fate Forecasting: A Data-Assimilation Approach to Predict Epithelial-Mesenchymal Transition. Biophysical Journal. doi:10.1016/j.bpj.2020.02.011 [Publisher Link]
  16. van Sebille, E., et al. including Hoffman, M.J. 2020. The physical oceanography of the transport of floating marine debris. Environmental Research Reviews. doi:10.1088/1748-9326/ab6d7d [Publisher Link]
  17. Hoffman, M. J., Zhang, B., Lanerolle, L. W. J., & Brown, C. W. (2020). Evaluating the benefit and cost of assimilating satellite sea surface temperature into the NOAA Chesapeake Bay Operational Forecast System using 4DVAR and LETKF. NOAA Technical Report, 39. [Publisher Link]
  18. Mason, S.A., J. Daily, G. Aleid, R. Ricotta, M. Smith, K. Donnelly, R. Knauff, W. Edwards, and M.J. Hoffman. 2020. High levels of pelagic plastic pollution within the surface waters of Lakes Erie and Ontario. Journal of Great Lakes Research. doi:10.1016/j.jglr.2019.12.012 [Publisher Link]
  19. Floyd, C., M.J. Hoffman, and E. Fokoue. 2019. Shot-by-shot stochastic modeling of individual tennis points. Journal of Quantitative Analysis in Sports. doi:10.1515/jqas-2018-0036 [Publisher Link]
  20. Greybush, S.J., et al. including M.J. Hoffman. 2019. The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0. Geosci Data J. doi:10.1002/gdj3.77 [Publisher Link]
  21. Parthasarathy, A., A.C. Tyler, M.J. Hoffman, M.A. Savka, and A.O. Hudson. 2019. Is Plastic Pollution in Aquatic and Terrestrial Environments a Driver for the Transmission of Pathogens and the Evolution of Antibiotic Resistance? Environ. Sci. Technol. doi:10.1021/acs.est.8b07287 [Publisher Link]
  22. Bachmann, C.M., et al. including M.J. Hoffman. 2019. A Low-Rate Video Approach to Hyperspectral Imaging of Dynamic Scenes. J. Imaging, 5(1), 6. doi:10.3390/jimaging5010006 [Publisher Link]
  23. Uzkent, B., Rangnekar, A., and M.J. Hoffman. 2018. Tracking in Aerial Hyperspectral Videos using Deep Kernalized Correlation Filters. IEEE Transactions on Geoscience and Remote Sensing, 57 (1), 449–461. doi:10.1109/TGRS.2018.2856370 [Publisher Link]
  24. Lobyrev, F. and M.J. Hoffman. 2018. A morphological and geometric method for estimating the selectivity of gill nets. Reviews in Fish Biology and Fisheries, 28. doi:10.1007/s11160-018-9534-1 [Publisher Link]
  25. 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, 27, 093911.
  26. Uzkent, B., M.J. Hoffman, and A. Vodacek. 2016. 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. doi:10.1109/JSTARS.2016.2560220
  27. 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
  28. 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. doi:10.1109/JSEN.2014.2346152
  29. 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.
  30. 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
  31. 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
  32. 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
  33. 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
  34. 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
  35. 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
  36. 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
  37. 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. Rangnekar, A., Kanan, C. and Hoffman M. J. (2023). Semantic Segmentation with Active Supervised Learning. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision. [Publisher Link]
  2. Rangnekar, A., Kanan, C. and Hoffman M. J. (2022). Semantic Segmentation with Active Semi-Supervised Representation Learning. 2022 British Machine Vision Conference.
  3. Mulhollan, Z., Gamarra, M., Vodacek, A. and Hoffman, M. J. (2022). Essential Properties of a Multimodal Hypersonic Object Detection and Tracking System. DDDAS2022 Conference, October 2022.
  4. Rangnekar, A., Ientilucci, E., Kanan, C., and Hoffman, M.J. (2022). SpecAL: Towards Active Learning for Semantic Segmentation of Hyperspectral Imagery.
  5. Rangnekar, A., Mulhollan, Z., Vodacek, A., Hoffman, M.J., et al. (2022). Semi-supervised hyperspectral object detection challenge results — PBVS 2022. CVPR Workshops. [Publisher Link]
  6. Rangnekar, A., Wong, C., Rochman, C., & Hoffman, M.J. (2022). On fine-grained micro-plastics classification — FGVC 2022. CVPR Workshops. [Publisher Link]
  7. Rangnekar, A., Yao, Y., Hoffman, M.J., & Divakaran, A. (2021). Fine-Tuning for One-Look Regression Vehicle Counting in Low-Shot Aerial Datasets. Pattern Recognition. ICPR International Workshops, pp. 5–18. Springer. [Publisher Link]
  8. Mulhollan, Z., Rangnekar, A., Vodacek, A., & Hoffman, M. J. (2020). Occlusion Detection for Dynamic Adaptation. Dynamic Data Driven Application Systems, pp. 337–344. Springer. doi:10.1007/978-3-030-61725-7_39
  9. Rangnekar A., Ientilucci E., Kanan C., Hoffman M.J. (2020). Uncertainty Estimation for Semantic Segmentation of Hyperspectral Imagery. DDDAS 2020, LNCS vol 12312. Springer. doi:10.1007/978-3-030-61725-7_20
  10. Mulhollan, Z., A. Rangnekar, T. Bauch, M.J. Hoffman, and A. Vodacek. 2020. Calibrated Vehicle Paint Signatures for Simulating Hyperspectral Imagery. CVPR Workshops, June 2020. [Publisher Link]
  11. Li, H., L. Pan, E.J. Lee, Z. Li, M.J. Hoffman, A. Vodacek, and S. S. Bhattacharyya. 2019. Hyperspectral Video Processing on Resource-Constrained Platforms. WHISPERS 2019, Amsterdam. doi:10.1109/WHISPERS.2019.8921138
  12. Rangnekar, A., & Hoffman, M. J. (2019). Learning representations to predict landslide occurrences and detect illegal mining across multiple domains. ICML 2019. [Publisher Link]
  13. 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.
  14. Uzkent, B., M.J. Hoffman, and A. Vodacek. 2016. Real-time Vehicle Tracking in Aerial Video using Hyperspectral Features. CVPR Workshop: Moving Cameras Meet Video Surveillance, June 2016. [Publisher Link]
  15. 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. doi:10.1016/j.procs.2015.05.358 [Publisher Link]
  16. Uzkent, B., M.J. Hoffman, and A. Vodacek. 2015. Efficient integration of spectral features for vehicle tracking utilizing an adaptive sensor. Proc. SPIE 9407, 940707. doi:10.1117/12.2082266 [Publisher Link]
  17. 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]
  18. Vodacek, A., J. P. Kerekes, and M.J. Hoffman. 2012. Adaptive optical sensing in an object tracking DDDAS. Procedia Computer Science, 9, 1159–1166. doi:10.1016/j.procs.2012.04.125
Book Chapters
  1. Hoffman, M.J., A. Rangnekar, Z. Mulhollan, and A. Vodacek (2023). DDDAS-Based Remote Sensing. In: Darema, F., Blasch, E.P., Ravela, S., Aved, A.J. (eds) Handbook of Dynamic Data Driven Applications Systems. Springer, Cham. doi:10.1007/978-3-031-27986-7_20
Commentary / Popular Press
  1. Hoffman, M.J. and A.C. Tyler (2018). Tons of plastic trash enter the Great Lakes every year — where does it go? The Conversation.
Conference Papers
  1. H. Li, L. Pan, Z. Li, M. J. Hoffman, A. Vodacek and S. S. Bhattacharyya. 2018. Design methods for hyperspectral video processing on resource-constrained platforms. Proceedings of the Hyperspectral Imaging & Applications Conference, pp. 2, October 2018.
  2. Uzkent, B., M.J. Hoffman, A. Vodacek, and B. Chen. 2015. Background image understanding and adaptive imaging for vehicle tracking. Proc. SPIE 9460, 94600F. doi:10.1117/12.2177494 [Publisher Link]
  3. 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. doi:10.1109/WNYIPW.2014.6999484 [Publisher Link]