Our department offers innovative undergraduate and graduate programs in computational science that impart a synergy among multi-disciplines, thus providing extensive, interdisciplinary hands-on training. We are a self-contained department, unusual among universities, whose faculty members consist of biologists, computer scientists, engineers, geneticists, geophysicists, material scientists, hydrologists, mathematicians, and physicists. Such a varied representation among disciplines opens doors for an even broader spectrum of research interests to be represented in the future.

Applied machine learning in medical imaging: prostate and breast cancer detection, personal diagnosis from clinical and image (MRI) data, improve generalization of models. Applied machine learning in earth sciences: data assimilation in ocean models, nowcasting (precipitation and hail), short-term forecast of air pollution, loop current and eddy detection and analysis.

Climate change: predicting future distribution of invasive insect pests considering climate change projections.

Scientific Machine Learning: Physics Informed Neural Networks (PINNs) to improve parameterizations in Ocean Models, etc.