Dan W Taylor BSc MIET

DOB: 5th April 1978 Email: dan@logicalgenetics.com

Based in Reading, UK

Summary

A highly motivated and skilled software development engineer with a flair for innovation and pragmatic attitude to system design. Accomplished in the field of biologically inspired computing: evolutionary algorithms, neural networks, artificial immune systems and other AI technologies. Experienced in object oriented programming, relational databases, user interface design and web development.

I enjoy working as part of a focussed and capable team, work well under pressure and love the thrill of a new challenge. I tend to employ a design-oriented approach to development and adhere to strict coding standards.

Key Skills

  • Six years experience of object oriented software design (Delphi, C#, some C++)
  • Artificial Intelligence development
  • Relational database design and maintenance (Firebird, MySQL)
  • Web development (HTML/XHTML, PHP, Javascript, CSS, XSLT)
  • Competent with Windows and Linux operating systems
  • Research skills
  • Competent and confident public speaker, won best presentation award at major conference
  • Keen to travel, full clean driving licence

Qualifications

After graduating from Reading University with a 2.1 in Cybernetics and Computer Science I began working towards a doctorate in Computer Science. My studies are on a part time basis and are due to be completed in 2006/2007. Key research areas include fault detection and prediction in time series data using biologically inspired computing techniques.

PhD Computer Science, Heriot Watt University, Edinburgh Ongoing
BSc Cybernetics and Computer Science, University of Reading 2000
A Levels Computing (A), Electronics (A), Chemistry (C) 1996

Employment History

JTL Systems Limited

Newbury, Berkshire, UK    (www.jtl.co.uk)

Software Development Engineer (2000 - Present)

JTL specialise in control and monitoring systems for commercial refrigeration, including the manufacture of control hardware and operation of a 24 hour Alarm Monitoring Centre. JTL's primary customer base is the supermarket industry.

I joined JTL as part of a TCS (now KTP) programme after the completion of my degree. The key objective of the TCS scheme is to facilitate the transfer of knowledge between academia and industry using a high calibre graduate as a conduit. The aims of my project were to investigate the use of artificial intelligence and data mining technologies in the field of commercial refrigeration. The project reached a successful conclusion in 2002 and was rated as one of the top ten TCS projects that year.

After the completion of my TCS project I have been employed by JTL on a full time basis. During my time at the company I have worked in a wide variety of challenging and exciting areas, taking a lead role in system design and project management.

Databases
I was key in the design of several mission critical relational databases, some of which have been in continual use for over five years and contain several million records.
Monitoring Centre Operator Software
Used to display targeted information on alarms to allow operators to make informed decisions on the appropriate course of action. Provides facilities to manage engineer callout by telephone, email or SMS. My responsibilities on this project included the development of the core object hierarchy, object persistence, database synchronisation and much of the user interface.
Web Reporting System
Provides customers with live access to targeted information via the internet. Based on atomic report objects, which allow new functionality to be added without recompilation. I was the sole developer on this project, taking responsibility for the development of the report design system and custom web server.

In addition to these traditional software products, my work also includes the ongoing development of several AI systems. To the best of my knowledge, these products are unique in their target marketplace.

Prediction Systems
Power usage, cabinet temperatures and suchlike can be predicted to a high degree of accuracy using neural network technology. This provides information both internally and for customers enabling better management of machinery and engineers.
Fault Detection Systems
The human immune system forms the inspiration for a novel fault detection system for refrigerated cabinets and associated machinery.

Publications

The following papers have been published in peer-reviewed academic literature as part of my PhD studies.

Innate and Aquired Immunity in Real Time Systems
Dan W Taylor, David Corne (2004)
An Investigation of the Negative Selection Algorithm for Fault Detection in Refrigeration Systems
Dan W Taylor, David Corne (2003)
Refrigerant Leak Prediction in Supermarkets Using Evolved Neural Networks
Dan W Taylor, David Corne (2002)
Predicting Alarms in Supermarket Refrigeration Systems Using Evolved Neural Networks and Evolved Rulesets
Dan W Taylor, David Corne, David Taylor, Jack Harkness (2002)