Dr. Mario Gongora

Research

Email:

Home: http://www.cse.dmu.ac.uk/~mgongora

My Research Interests.

• Evolutionary programming,
• Modelling and simulation using Computational Intelligence,
• Intelligent Mobile Robots and Bioengineering.

Current Projects

• Intelligent agent behaviour in artificial environments.
• Simulation of Customer Behaviour in large venues using Evolutionary Agents.
• On-line path optimisation using self simulation and genetic paradigm.
• Path search for migrations of ancient populations using analysis of mDNA.
• Analysis of Developmental Genetics Theory using Evolutionary Programming.

Current PhD fields of Research

• Evolution and encoding of Behaviour for multiple agents or robots: This involves research in collaborative behaviour of robots, distributed intelligence and evolving intelligent agents; considering for real or artificial environments.
• Robot interaction and enhanced control using vision and sound: This area relates to the use of sound and vision in novel ways to enhance the control of robots (including system identification tasks). It realtes also to using these novel techniques to enable efficient interaction between robots and the environment, other robots or users. An interdisciplinary aspect of this research is focused toward using sound and visual expressions as a means for robots to interact with non technical users.
• Continuous system optimisation using self-simulation: Just like animals (and humans) adapt to changes on their own body (as they grow, age or have accidents or illness) and also to changes in their external environment, we are working in robotic control systems that evolve with the robot and adapt continuously to changes either in its own hardware (change, addition or deterioration of parts, wear and tear, changes in energy availability, etc...) or its environment.
• SRY gene analysis: Using evolutionary programming techniques, we are studying the correlation between the DNA structure of the SRY gene (Sex Determining Region in the Y chromosome) and the sexual characteristics of the individuals. Work needs to be done in the data analysis of mutations of the SRY gene and the associated effects in the phenotype of the individual.
• Analysis of Left-Right Asymmetry in Mammals: Using simulations of basic artificial embryology with cellular automata, the theories on how mammals develop their Left/Right asymmetry are studied. Evolutionary programming is used to evolve cellular automata that develop in colonies with asymmetric characteristics; work is being carried out to evolve and correlate this asymmetry with the same theories as in biological systems.

Virtual Romans:The Virtual Romans project at the IOCT.