I am a researcher using in-silico modelling and Artificial Intelligence principles to predict the landscape-scale movement of foraging bumble bees. Primarily, my focus is the risk assessment of bee-mediated gene escape from GM crop varieties in agricultural landscapes. My model can also be used to determine suitable landscape configuration scenarios that would promote bee activity, thereby potentially aiding urgent conservation measures.I have designed and implemented a computer simulation, HARVEST (Harvesting Animals with Reinforced Values and ESTimates) using the Python programming language. The model is based on first principles of bumble bee behaviour, and uses techniques derived from the Reinforcement Learning branch of Artificial Intelligence. The model has achieved considerable success in predcting real world bee behaviours.I have generated interest with both the Ecological Society of America and the Rank Prize Fund, and have presented my work both to the ESA and the British Ecological Society. I have been invited to talk at the 2010 Rank Prize Fund symposium on pollination.Specialties: Software Development,Artificial Intelligence and Machine Learning,Pollinator Dynamics,Project Management,Oral Presentation