I'm not in the United States. I am in the Visualization group at the Institute of Computer Science (Institutt for informatikk) in Bergen, Norway. It is one of the handful of research groups cooperating on data visualization in Europe, and is a very international research group. I think me and one of our PhD students are the only native Norwegians at the moment. We have a Turk, two Swiss, an Italian, a Russian, and a couple of other nationalities. Prominently, Vienna has another good visualization group and I am pretty sure that UC Berkley has one. (Ben Shniderman's, maybe?). I am currently the only Masters student in this group, we get almost no applicants.
Would warmly recommend it. Visualization is a very large field, so you'll have to carve out some niche. I am in information visualization, which is the branch most generally applicable if you want to do data mining-related things. But there are many other variants: Visualization of scientific/simulation data, e.g. flow rendering, combustion processes, climate simulation, as well as medical fields: CT/MRI volume rendering, real-time 3D ultrasound and quite a few others. Central themes at the moment are using GPUs to implement more advanced 3D volume rendering techniques, or even using GPUs to draw data which is not 3D but where there are performance issues when using CPU alone. For instance, drawing dynamic (25FPS, interactive) scatterplots of large (>1 million records) datasets.
I guess the definition of a "large" dataset varies by context, in visualization you hit this limit earlier than in statistics and non-visual data mining if you use "discrete" methods where every item is drawn on screen.
Would warmly recommend it. Visualization is a very large field, so you'll have to carve out some niche. I am in information visualization, which is the branch most generally applicable if you want to do data mining-related things. But there are many other variants: Visualization of scientific/simulation data, e.g. flow rendering, combustion processes, climate simulation, as well as medical fields: CT/MRI volume rendering, real-time 3D ultrasound and quite a few others. Central themes at the moment are using GPUs to implement more advanced 3D volume rendering techniques, or even using GPUs to draw data which is not 3D but where there are performance issues when using CPU alone. For instance, drawing dynamic (25FPS, interactive) scatterplots of large (>1 million records) datasets.
I guess the definition of a "large" dataset varies by context, in visualization you hit this limit earlier than in statistics and non-visual data mining if you use "discrete" methods where every item is drawn on screen.