Çağatay Demiralp
I am currently a postdoctoral scholar in the Computer Science Department at Stanford University.
I had been a PhD student in the Computer Science Department at Brown University last six years. My interests lie in developing mathematical and computational models, algorithms, and interactive tools to explore, understand, and characterize patterns and structures in data. To this end, I often use insights and techniques from data visualization, computer graphics, statistical machine learning, geometry, and topology. This decidedly both qualitative (e.g., visualization, topology) and quantitative approach is exemplified in my PhD research. The focus of my thesis work had been computational brain connectivity, where I model, visualize, and analyze structural brain connectivity at the scale provided by diffusion imaging (here is my CV).
Speaking of qualitative characterization of data, I TA'ed the very first Computational Topology class taught at Brown. The course material is rather interesting--see my Conduit article on it.
Recently, I have also been thinking on a visualization model based on structure-preserving maps. Filling in the gaps in the model will take some time but check out our panel at VisWeek if you want to learn about the general idea.
Last semester (Fall 2011), I have interned with Machine Learning and Perception Group at Microsoft Research Cambridge; there I worked with Antonio Criminisi on semantic segmentation of brain tumors.
The development story behind the two-dimensional brain maps project appears in Visual Strategies.
