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Algorithms and geometry

Geometric datasets are becoming common with popularity of GPS and other location services. Many types of data are geometric with embedding in a Euclidean space such as the plane or 3D space. 

We want to develop efficient algorithms to process and answer questions about geometric data, particularly in dynamic scenarios when the dataset is updated frequently or contains noisy, uncertain information. 

Different types of computational and mathematical concepts are relevant to these topics: geometry, topology, streaming algorithms, metric embedding, randomization and many others. The results can be useful in various fields from mobile computing to databases. 

Potential Supervisor

Rik Sarkar





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