My research straddles (1) computation of imaging-based science and (2) fundamentals of data visualization.

(1) Science pairs measurement tools that produce experimental data with computational tools to process the data. Advances in scanned imaging modalities (CT, MRI, microscopy, etc) are constantly increasing in speed, resolution, and sensitivity. Research in collaboration with physical and biomedical researchers -- who acquire image data to answer scientific questions -- can advance how this data may be visually and quantitatively analyzed.

(2) It is an exciting time to try to develop the theoretical underpinnings of data visualization. As the discipline matures, we can develop increasingly detailed theoretical accounts of how effective data visualizations are designed, implemented, and perceived. Stretching visualization to new and fast-changing applications (particularly machine learning), however, challenges the coherence of vis theory.

I look for students who, like me, are excited by the prospects of improving how science is computed, or advancing the theory and practice of data visualization. See my information about applying.