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Dr. Chérubin is a physical oceanographer specialized in the understanding of ocean dynamics, which is the study of why the water moves the way it moves. It establishes the connection between forces that act on the ocean, such as gravity, the earth’s rotation, the wind, the moon and the heat from the sun, and the water motions. His research has focused on dynamics of motions associated with instabilities in coastal currents and eddies, using both analytical and numerical models in the quasi-geostrophic, shallow-water formalisms, and in realistic models. This research provides a deep understanding of the environmental forces that affect ocean ecosystems at multiples levels of the trophic chain. Both observational analysis and numerical modeling involving hydrodynamic (the Regional Oceanic Modeling System - ROMS) and biophysical models (Connectivity Modeling System - CMS and Ichthyop) are used to study how environmental drivers shape the oceanic ecosystems.

2025

Bang, C., Altaher, A.S., Zhuang, H., Altaher, A., Srinivasan, A., & Chérubin, L.M. (2025). Physics-informed neural networks to reconstruct surface velocity field from drifter data. Front. Mar. Sci., 12:1547995. doi: 10.3389/fmars.2025.1547995.

Carvalho, J., Chérubin, L.M., & O'Corry-Crowe, G. (2025). Autonomous wave gliders as a tool to characterize delphinid habitats along the Florida Atlantic coast. PeerJ, 13:e19204. http://doi.org/10.7717/peerj.19204.

Chérubin, L.M., Woodward, C., Schärer-Umpierre, M., Nemeth, R.S., Appeldoorn, R., Appeldoorn-Sanders, E., Tuohy, E., & Ibrahim, A.K. (2025). Assessing red hind (Epinephelus guttatus) spawning aggregation changes from long-term relative variations in call types associated with reproductive behaviors. ICES Journal of Marine Science, 82(8), fsaf138. http://doi.org/10.1093/icesjms/fsaf138.

Van Horn, C.J., Candelmo, A.C., Heppell, S.A., McCoy, C.R.M., Pattengill-Semmens, C.V., Waterhouse, L., Chérubin, L.M., et al. (2025). Hydrophone Placement Yields High Variability in Detection of Epinephelus Striatus Calls at a Spawning Site. Ecological Applications, 35(5): e70081. http://doi.org/10.1002/eap.70081.

2024

Muhamed Ali, A., Zhuang, H., Huang, Y., Ibrahim, A.K., Altaher, A.S., & Chérubin, L.M. (2024). Ocean Currents Velocity Hindcast and Forecast Bias Correction Using a Deep-Learning Approach. J. Mar. Sci. Eng., 12, 1680. http://doi.org/10.3390/jmse12091680.

Ibrahim, A.K., Zhuang, H., Schärer-Umpierre, M., Woodward, C., Erdol, N., & Chérubin, L.M. (2024). Fish Acoustic Detection Algorithm Research: a deep learning app for Caribbean grouper calls detection and call types classification. Front. Mar. Sci., 11:1378159. doi: 10.3389/fmars.2024.1378159.

2023

Woodward, C., Schärer-Umpierre, M., Nemeth, R.S., Appeldoorn, R., & Chérubin, L.M. (2023). Spatial distribution of spawning groupers on a Caribbean reef from an autonomous surface platform. Fisheries Research, 266, 106794. http://doi.org/10.1016/j.fishres.2023.106794.

Altaher, A.S., Zhuang, H., Ibrahim, A.K., Muhammed Ali, A., Altaher, A., Locascio, J., McCallister, M.P., Ajemian, M., & Chérubin, L.M. (2023). Detection and localization of Goliath grouper using their low-frequency pulse sounds. The Journal of the Acoustic Society of America, 153(4), 2190-2202. http://doi.org/10.1121/10.0017804.

Brewster, L.R., Ibrahim, A.K., Locascio, J., DeGroot, B.C., Chérubin, L.M., & Ajemian, M.J. (2023). Seasonal Dynamics and Environmental Drivers of Goliath Grouper (Epinephelus itajara) Sound Production. Fishes, 8, 293. http://doi.org/10.3390/fishes8060293.