Rick Fawley

Postgraduate Research Student
School of Computer Science and Electronic Engineering (CSEE)
 Rick Fawley


Ask me about
  • Unsupervised clustering and machine learning


I am a distance learning, PhD student, working in industry, as a technologist. I am a Fellow of the Institution of Analysts and Programmers (FIAP), a Chartered IT Professional Fellow of the British Computer Society (CITP FBCS), and a Member of the Institution of Engineering and Technology (MIET). I work as a technology architect, specialising in smart buildings, video analytics, biometric access control systems, and colleague experience technologies. I am familiar with data centre architecture, Azure and Google Cloud, Linux, i-Series and z-Series mainframes, and I programme in a variety of languages. I am ITIL, TOGAF and PMP certified.


  • MSc Data Science & Analytics (Distinction) The University of Hertfordshire (2023)

  • BSc(Hons) Computer Science (First) The University of Hertfordshire (2020)

  • DipMath (Distinction) The Open University (2002)

Research and professional activities


Optimised feature weighting and noise removal for unsupervised machine learning clustering

The research considers the Weighted K-Means algorithm with distributed centroids aimed at clustering data sets with mixed continuous and categorical data types, with a proposal to allow detected or nominated features to have different significance, or weight, in different clusters. This approach supports the notion that features used for clustering may have different bearing, based on context, and combines n-dimensional geometric measures with pseudo density concepts.

Supervisor: Dr. Renato Cordeiro de Amorim

Research interests

Automatic feature weighting in clustering of large data sets

Unsupervised feature selection



Colchester Campus

Working pattern:

I'm a distance learning student, so not generally on campus, and seldom working traditional office hours