About Dr Ken McGarry
I'm an Associate Professor of Computer Science research. I teach programming, statistics, computer science, data mining, and research methods to undergraduate and postgraduate students.
My research interests include the investigation of machine learning techniques for detecting anomalous patterns for knowledge discovery. Anomaly detection can reveal interesting patterns that are on the boundary between noise and useful discoveries. I also perform data analysis of medical and biostatistical information and constructing statistical models for prediction and interpretation. I work with medical professionals in the NHS and with staff in Health Sciences.
My other interests include drug repositioning using chemical similarity, drug side-effects, protein on and off-targets – again using computational methods such as complex network theory, clustering, and inferential statistics.
I am a Senior Fellow of the Higher Education Academy and a Fellow of the British Computer Society.
Teaching and supervision
I teach computer science across a variety of undergraduate and postgraduate modules. I lead a number of modules including:
- Data Science Fundamentals
- Technology Management for Organisations
- Business Analytics
Research
My interests include data mining and knowledge discovery from databases, especially bioinformatics data. I'm also fascinated by the so-called "interestingness" measures which are used to uncover the most useful patterns from the data mining process.
I am also interested in drug repurposing using computational methods and various publicly available databases.
Potential topics for those wishing to undertake a PhD (computer-based):
I'm open to discussions with prospective students which include machine learning and data mining techniques:
- Modifications to existing data mining algorithms in order to improve effectiveness or scope
- Creation of intelligent hybrid systems, using a combination of machine learning techniques for a variety of applications
- Text mining and sentiment analysis on a variety of topics
- Analysis of drug/disease comorbidity data for pharmacovigilance
- Complex networks (graph theory) of disease and connectivity patterns
- Developing novel "interestingness" methods for anomaly detection and methods for the "interpretability" of machine learning models.
- Developing novel methods for Explainable AI (XAI), a very important topic since deep learning and other methods ought to have their decisions made transparent i.e. why did they class a particular patient as either healthy or unhealthy or award a bank loan or decline to give one?
Over the past 20 years, I have published over 100 papers. These are in conjunction with University of Sunderland staff, several PhD, BSc, MSc students, and a wide range of external collaborators including academic, medical, commercial, and industrial partners.
Current PhD research students:
- Bamidele Ajayi
- David Grey
- Guendalina Caldarini
- Liz Gandy
- Amer Hosy
- Simin Baloochzadeh
- Andrews Kyeremeh
- Marek Sviderski
- Yusuf Albasri
Past PhD research students:
- Obruche Emueakporavwa
- Victor Thompson
- Tom Drange
- Heather Garthwaite
- Nabeel Khan
- James Malone
- Normon Solomon
- Chih-Fong Tsai
- Galal Omar
- Muhammad Naveed Anwar
- Walid El-Quirem
- Usama Ben-Hamid
- Jeff Evans
- Nusirat Bello
- Jill Jobson
- Egwu Ilkenna
- Thomas Cherian
- Reza Modfi
- Ashraf Saleh
Areas of expertise
- Data analysis (predictive modelling)
- Medical statistics (basic analysis, meta-analysis, survival analysis)
- Bioinformatics (sequence analysis, proteomics)
- Data mining (classification, clustering, association rules)
- Machine learning (Bayesian networks)
- Big Data
Further information
- Senior Fellow of the Higher Education Academy
- Fellow of the British Computer Society
Recent professional activities:
- Member of the Editorial Board for Neural Computing and Applications Journal
Reviewer for the following journals:
- PLOS ONE
- Expert Systems
- Knowledge-Based and Intelligent Engineering Systems
- Neural Computing Applications
- IEEE Transactions on Neural Networks and Learning Systems
- Computer Methods and Programs in Biomedicine
- Medical and Biological Engineering and Computing
- Int J. on Artificial Intelligence Tools (IJAIT)
Reviewer for UK Research Councils:
- BBSRC Tools & Resources fund
- EPSRC
- MRC grants
- NIHR grants
- Diabetes UK
Reviewer for Overseas Research Councils:
- USA NSF grants
- Israeli Ministry of Science and Technology
For details of publications and other information see my Orcid record(opens in new tab).