computational model

Insect-brain inspired neuromorphic nanophotonics
The goal of the project is to develop nanophotonic on-chip devices for integrated sensing and neural computation, inspired by the insect brain.
Insect-brain inspired neuromorphic nanophotonics
An incentive circuit for memory dynamics in the mushroom body of Drosophila melanogaster
Modelling differential roles for identified dopaminergic and output neurons of the fruit-fly mushroom bodies combined with a novel dopaminergic plasticity rule explains neural and behavioural phenomena in olfactory learning tasks.
Evripidis Gkanias, Li Yan McCurdy, Michael N. Nitabach, Barbara Webb
An incentive circuit for memory dynamics in the mushroom body of Drosophila melanogaster
Insect neuroethology of reinforcement learning
Thesis - Doctor of Philosophy. I inversigated how insects form associative memories in their mushroom bodies and how this impacts their olfactory learning, visual navigation, and time-delayed reinforcements tasks.
Insect neuroethology of reinforcement learning
Exploiting invisible cues for robot navigation in complex natural environments
Design a sensor that transforms skylight into a compass direction.
Exploiting invisible cues for robot navigation in complex natural environments
Miniature insect model for active learning (minimal)
We develop a new foundation for understanding natural learning by developing a complete multilevel model of learning in larvae
Miniature insect model for active learning (minimal)
Robocrab: data-driven adaptation of the evation behaviour in fiddler crabs
Disertation - Master of Science. We create a semi-supervised structure of neural network, inspired by the physiology of neurons in fiddler crabs, and train it to adapt the evasion behaviour of fiddler crabs on potential predators, solving a complicated visuomotor problem (developed in Python using the Theano/Tensorflow-based ‘keras’ library
Robocrab: data-driven adaptation of the evation behaviour in fiddler crabs