Mike graduated his degree in Computer Science from the University of Exeter in 2011, where he investigated Genetic Algorithm (GA) methods for tackling the traveling salesman problem. He completed his PhD in Computer Science in 2015 also from the University of Exeter, where he investigated the use of Genetic Programming (GP) for the creation of Cellular Automata (CA) state transition rules. This work investigated the GPCA method’s use for theoretical CA such as the Game of Life, and also for Real-world systems, specifically Urban flood modelling. In his thesis, he also investigated the use of highly parallel hardware in multi-core CPU and many-core GPU, using the OpenMP and OpenCL API's respectively. He now continues his work with the Centre for Water Systems within the University of Exeter, with a Knowledge Transfer Partnership (KTP) project were he is responsible for, and contributes the CADDIES framework, and its integration in to industrial partner’s systems, while also furthering research in the area of high speed modelling.

During his time with the Centre for Water Systems, and Mike has worked with colleagues on a number of other projects including: Dr Andrew Duncan – RAPIDS projects - Artificial Neural Networks (ANN) for sewer system flood prediction, Dr Ed Keedwell and Dr Ahmed Kheiri – SEQA – Sequence Analysis based hyper-heuristics for water distribution systems, Luis De Sousa - Swiss Federal Institute of Aquatic Science and Technology (EAWAG) – CADDIES – Hexagonal grid API.

Student outreach, and research activities:

Mike has been a supervisor for young adults attending the SmallPeice Computer Science and Artificial Intelligence (AI) course at Exeter university since 2011, where young engineers are introduced to Ai through fun activities such as Big-Tracks Robots, Lego Mind-Storm Robots, and RoboCode challenges. Mike has also been active in the Computer Science dept.’s undergraduate open days since 2011, demonstrating CA projects, Pi-Bot, and once again supervising team RoboCode challenges. Mike also assisted with the 2011 Loebner Prize in AI, which sets the world’s best Ai against the Turing Test.

Teaching:

Mike has been a teaching assistant and coursework marker for a number of undergraduate course, over several years.

ECM1408/09 - Programming for Science/Business (Teaching Python coding) 2011-2015

ECM3412 – Nature inspired computation (ANN and GA concepts) 2012-2015

Spare Time/Hobbies/Research interests:

Mike enjoys playing badminton and swimming, and even cooking cakes in his spare time. Current side project including a Pi-Bot (and machine learning possibilities), learning to the use the games engine Unity, Virtual Reality through mobile smart phones.