Admissions are open for starting in 2017. See below for various topics and PhD positions. Students are strongly advised to apply by Early December.
Networked systems are crucial in modern science and technology. For eaxmple, www and search engines, social networks, communication, road networks and transportation, all depend on networked systems and analysis of networks. The topic also shows up in biology, physics, finance, economics, linguistics and many other areas. We are thus interested in developing techniques to better understand such systems through their networks, to make them more efficient, adaptable and effective.
We want to extract communities, influential nodes and summaries of these networks and understand properties of these networks in various other ways. See the STN course for information.
Geometric techniques are fundamental to computing. In this topic, we are interested in applying geometry and topology for data mining. For example, mobility and sensor data can be handled better with these techniques. We are particularly interested in gemteric machine learning techniques such as clustering and persistent topology.
Large volumes of data are available from mobile phones and their sensors. This data can be used to infer actions and movements of users. We can thus obtain fine-grained information about the society, traffic and environment.
This topic is about using mobile, IoT and sensor data to draw of higher level inferences, using machine learning, data mining and theoretical ideas.
See here for instructions.