Birmingham City University, Technology Innovation Centre.

Professor Keith Osman has extensive experience of systems modelling, and pervasive computing within engineering and their application within other disciplines.  Particular focus is on the application and development of artificial neural networks (ANNs) as predictive models, training ANNs to identify common processes, the ranges of processes involved and comparisons of ANN performance with statistical and other methods. He is experienced in research contracts, as Principal-Investigator on the EPSRC grant GR/J17463/01 - Artificial Neural Networks For Monitoring Of Resistance Spot-Welding Of Aluminium (in collaboration with Alcan International and Smiths Industries) involving - the training of neural networks, using the trained ANNs to predict the outcomes from process data, training ANNs to identify a range of common process disturbances. 

He is collaborating with arts and humanities disciplines (Birmingham City University, BIAD - current grant EPSRC EP/D062160/1 Durable and Permanent Product Authentication and Anti-Theft Marking, DTI Ref. TP/4/AMD/6/S/22052) concerning  anti-counterfeit technology, novel clone-proof 2D matrix-codes and the potential for direct-writing of EAS and RFID antenna structures. This project is part of a larger DTI Direct-Initiative programme led by CERAM and includes 6 industrial partners.