University Positions:

06/2018 - present — Postdoctoral Researcher, College of Marine Science, University of South Florida, USA

Education:

06/2018 College of Marine Science, University of South Florida, Ph. D Degree in Marine Science

08/2013 - 06/2018 — College of Marine Science, University of South Florida (Ph. D Candidate)

09/2012 - 06/2014 — School of Remote Sensing and Information Engineering, Wuhan University. (Master of Engineering)

09/2008 - 06/2012 — School of Remote Sensing and Information Engineering , Wuhan University. (Bachelor of Engineering)

Selected Publications:

Putman, N. F., G. J. Goni, L. J. Gramer, C. Hu, E. M. Johns, J. Trinanes, and M. Wang (2018). Simulating transport pathways of pelagic Sargassum from the Equatorial Atlantic into the Caribbean Sea. Progress in Oceanography, 165:205-214.

Long, J. S., C. Hu & M. Wang (2018) Long-term spatiotemporal variability of southwest Florida whiting events from MODIS observations, International Journal of Remote Sensing, 39:3, 906-923, DOI: 10.1080/01431161.2017.1392637.

Qi, L., Hu, C., Wang, M., Shang, S., & Wilson, C. (2017). Floating algae blooms in the east china sea. Geophysical Research Letters.

Lu, Y., Zhou, Y., Liu, Y., Mao, Z., Qian, W., Wang, M., ... & Du, P. (2017). Using remote sensing to detect the polarized sunglint reflected from oil slicks beyond the critical angle. Journal of Geophysical Research: Oceans, 122(8), 6342-6354.

Wang, M., & Hu, C. (2017). Predicting Sargassum blooms in the Caribbean Sea from MODIS observations. Geophysical Research Letters

Hu, C., Murch, B., Barnes, B. B., Wang, M., Maréchal, J-P., Franks, J., Lapointe, B. E., Goodwin, D. S., Schell, J. M., & Siuda, A. N. (2016). Sargassum watch warns of incoming seaweed, Eos, 97, doi:10.1029/2016EO058355.

Wang, M., & Hu, C. (2016). Mapping and quantifying Sargassum distribution and coverage in the Central West Atlantic using MODIS observations. Remote Sensing of Environment, 183, 350-367. http://dx.doi.org/10.1016/j.rse.2016.04.019

Wang, M., & Hu, C. (2015). Extracting Oil Slick Features From VIIRS Nighttime Imagery Using a Gaussian Filter and Morphological Constraints. IEEE Geoscience And Remote Sensing Letters, 12(10), 2051-2055. DOI : 10.1109/LGRS.2015.2444871.

Hu, C., Chen, S., Wang, M., Murch, B., & Taylor, J. (2015). Detecting surface oil slicks using VIIRS nighttime imagery under moon glint: A case study in the Gulf of Mexico. Remote Sensing Letters, 6(4), 295-301. http://dx.doi.org/10.1080/2150704X.2015.1029092

Computer Skills:

• C/C++ programming
• ENVI4.8
• ERDAS9.2
• ArcGIS9.3
• CorelDraw9.0
• Adobe Photoshop CS5
• Microsoft SQL Server2008
• Auto CAD2007