PhDs in: Social and technological networks; mobile and sensor computing; spatial computing; Algorithms and Geometry

Dr. Rik Sarkar

Admissions are open for starting in 2017. See below for various topics and PhD positions. Students are strongly advised to contact immediately and apply by early December, preferably sooner.

Social and technological networks

In an interconnected world, networks underlie all our social and technological systems. Examples of interconnected systems range from social networks and Internet to road networks and power grids. The increasing availability of data is now making it possible to analyse these networked systems at a high resolution and to look for patterns in their behaviour. Network science is the multidisciplinary subject spanning mathematics, informatics, physics and statistics that studies properties of networks and their relation to complex systems. See the STN course for more information.

Computational geometry, topology, clustering, and algorithms

Geometric techniques are fundamental to computing. In this topic, we are interested in applying geometry and topology for data mining. For example, spatial and sensor data can be handled better with these techniques. We are particularly interested in geometric information processing techniques.

Mobility and sensing

Internet of things is emerging as the omnipresent computing platform. We already have mobile devices present almost everywhere, and now we are seeing sensors and small computers being embedded in everything from buildings to cars. These devices can produce large quantities of data that is challenging to process and store. Fast inference is critical in keeping up with the stream of data from millions of sensors. Our goal is to develop methods to handle data and analysis rapidly, on demand.

Application process

See here for instructions.