Richard Correro is an undergraduate student at Stanford, majoring in mathematics and computational science. He is working this summer with COS to design machine learning systems to analyze satellite imagery of the Earth’s oceans toward combatting illegal fishing.
This work is part of Stanford’s Data Science Institute, which advances data science methods and tools to respond to our most pressing societal and scientific challenges, and Stanford’s Undergraduate Summer Research in Statistics, which provides an opportunity to undergraduate students to engage in interdisciplinary research using statistical methods. The project is a collaboration between COS staff (Shin Nakayama, Fiorenza Micheli, Elizabeth Selig, Colette Wabnitz, and Jim Leape), Trevor Hastie (Statistics) and Serena Yeung (Biomedical Data Science, Computer Science and Electrical Engineering).
Read the full Q&A here: https://oceansolutions.stanford.edu/stories-events/qa-vessel-tracking-machine-learning