Postgraduate Studentships
Proposed Project Title: Graph-based streaming data mining
Principal Supervisor: Prof Weiru Liu

Project Description:

Streaming data analytics in large sensor networks is increasingly important due to both the volume of data collected and the real-time decision making nature. Cyber-physical systems, social networks/social media, smart grids, smart transport systems are just few examples of large, distributed sensor networks that would benefit from real-time streaming data analytics for achieving situation awareness.

This project continues the existing work developed in KDE on graph-based data mining for both historic data and online streaming data. The primary areas to investigate are anomaly detection and concept drifting in a single sensor data stream and across multiple sensor data streams. Anomalies represent unusual situations that may need further investigation whilst concept drifting research is about how to discover gradual situation changes that occur over time, which may appear as anomalies in the first instance.

Objectives:

The key objectives are:

1. Understand the current state-of-the-art research in relevant areas. Conduct a comprehensive literature review.
2. Develop approaches for modeling single data stream anomalies, especially numerical data streams.
3. Develop approaches for correlating data streams for anomaly detection using graph-based methods for both numerical anomalies and structural anomalies.
4. Develop approaches for detecting concept drifting.
5. Evaluate proposed approaches with simulated, benchmark and real-world datasets in various applications.
6. Publish research papers at top level conferences and journals in relevant areas.

Academic Requirements:

A minimum 2.1 honours degree or equivalent in Computer Science, Computer Engineering, Mathematics, Statistics or other relevant degree is required. Applications that show relevant research experience (e.g. at Masters level) will be preferred. English Language Testing System (IELTS) 6.0 with a minimum of 5.5 in all four elements of the test or equivalent.

GENERAL INFORMATION

This 3 year PhD studentship, potentially funded by the Department for Employment and Learning (DEL), commences on 1 October 2015.

Eligibility for both fees and maintenance (£13,863 in 2014/15, 2015/16 TBC) depends on the applicants being either an ordinary UK resident or those EU residents who have lived permanently in the UK for the 3 years immediately preceding the start of the studentship. Non UK residents who hold EU residency may also apply but if successful may receive fees only.

Please note: DEL awards are available for Home and EU candidates only.

Applicants should apply electronically through the Queen’s online application portal at:
https://dap.qub.ac.uk/portal/

Further information available at:
http://www.qub.ac.uk/schools/eeecs/StudyattheSchool/PhDProgrammes

Contact detail

Supervisor Name: Prof Weiru Liu
Tel: +44 (0)28 9097 4896

QUB Address:
Computer Science at Elmwood, ECS1
Email: w.liu<στο>qub.ac.uk
Elmwood Avenue, Belfast BT9 6AZ

Deadline for submission of applications is 27th February