Postgraduate Studentships
Proposed Project Title: Robust Treatment of Missing Data
Principal Supervisor: Dr Cassio P. de Campos

Project Description:

Missing values are present in many types of data from a wide range of disciplines. Their treatment is a very common problem in statistical analysis of clinical and biological data. It has been shown that missing values in the data can severely affect subsequent experiments and results. When data is obtained from biological experiments, missingness might be due to the occurrence of imperfections during the experiment, insufficient machinery/reading resolution, dust or scratches on the slide, as well as other failures in the process.

This project regards the study of existing methods to deal with incomplete data. The goal is to build a novel robust method that will combine available data and results from existing state-of-the-art methods to yield more accurate estimates for the missing values. Algorithms will be experimented on multiple real-world data sets with clinical and genomic data of cancer patients, among others. Collaborations with biologists and medical doctors will bring the developments of this project to important real-world applications. Well-known as well as novel methods will be compared using the incomplete data sets to show the advantages and disadvantages of different approaches. Finally, sensitivity analysis can help to understand the results.

Objectives:

The objective of the project will be to develop and evaluate methods for robust treatment of missing data, as well as extensive empirical analyses using biomedical data sets. Standard methods from literature will be implemented and extended to address robustness issues. Novel approaches combining information from multiple sources (multiple data sets, output of other methods, expert’s knowledge) shall be created and their sensitivity analyzed. The algorithmic and data complexity of the methods are to be studied and compared to state-of-the-art approaches.

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: Dr Cassio P. de Campos
Tel: +44 (0)28 9097 6795
QUB Address: Computer Science at Elmwood, ECS1
Email: c.decampos<στο>qub.ac.uk
Elmwood Avenue, Belfast BT9 6AZ

Deadline for submission of applications is 27^th February 2015

For further information on Research Area click on: http://www.qub.ac.uk/research-centres/KDE/