The principal goal of my project is to investigate how insects acquire and retrieve memories, adapt to their environment and update their behaviour using their mushroom bodies (MB), with application in robotics. I will approach this problem by working in parallel on modelling the MBs using reinforcement learning (RL) methods as a general framework continuously increasing the biological constraints (top-down), and build the most bio-mimetic MB network possible and increase the level of abstraction (bottom-up), aiming to converge in a solution helpful for both the cognitive neuroscience and machine learning fields. More specifically, from the top-down approach, I expect the RL frameworks to give insights about the dopaminergic (DA) signal in the MB, and the bottom-up to provide novel RL learning rules. Using this piece of research, I aim to contribute to building fast and robust reinforcement learning systems for robotic applications and at the same time give insights into how insects form and use memories.
During his bachelor thesis in 2013 at the Aristotle University of Thessaloniki, Evripidis had his first experience in machine learning and artificial intelligence, under the supervision of Dr Grigorios Tsoumakas; he explored the performance of Deep Belief Networks (DBNs) on multi-label classification problems, including medical, image, sound and text datasets. In July 2013, he achieved the 1st class honours BSc degree in the same university with specialisation in Information Systems. In May 2014, Evripidis started working as a research assistant on human motion analysis at the Centre of Research and Technology - Hellas (CERTH) under the supervision of Dr Petros Daras, when he realised his passion for research. He was working on motion analysis of athletes performing sports, trying to use machine learning to train a coach that gives hints of how to improve their performance. Later, in September 2015, he decided to extend his knowledge of artificial intelligence by joining a homonymous master programme at the University of Edinburgh under the UK/EU masters scholarship awarded from the same university. It was then when he met Prof. Barbara Webb, who introduced him to the multidiscipline field of bio-robotics and insect robotics. She supervised his master thesis, where he successfully tried to model the evasion behaviour of the Australian fiddler crabs using a data-driven approach and semi-supervised learning. He graduated with distinction from the School of Informatics awarding the specialisation of Machine Learning in September 2016. Right after, he started working on building a robot that imitates the olfactory learning mechanism of the Drosophila larva with professor Webb as his advisor. While in the same institute, in March 2017 he started working on designing and modelling the celestial compass neural mechanism of the desert ants, under the same advisor and in collaboration with the University of Lincoln and the University of Sheffield (Dr Michael Mangan). His passion for the function of insect brains, bio-robotics and computational modelling led him to enrol the ECR in September 2018, when he started his PhD. He is currently fascinated by the function of the mushroom body in the insect brain, how memories are established there and its multimodal integration mechanism. Therefore, he tries to understand and model it using computational intelligence mechanisms under the supervision of professor Webb.
Probabilistic Machine Learning, Information Theory, Multimodal Integration, Computer Vision, Learning and Adaptation
2015 - 2016 ⚮ MSc in Artificial Intelligence and Machine Learning (with Distinction), the University of Edinburgh, United Kingdom
2008 - 2013 ⚮ BSc (Hons) in Computer Science and Information Systems, Aristotle University of Thessaloniki, Greece
2017 - 2018 ⚮ Research Associate, the University of Sheffield and the University of Edinburgh, UK
2016 - 2017 ⚮ Research Assistant, the University of Edinburgh, United Kingdom
2014 - 2015 ⚮ Research Assistant, Centre of Research and Technology - Hellas (CERTH), Greece
2019. November. From skylight input to behavioural output: a computational model of the insect polarised light compass. In International Navigation Conference. Edinburgh, UK
2017, July. Predator Evasion by a Robocrab. In Conference on Biomimetic and Biohybrid Systems, Stanford University, CA.
Gkanias, E., Scaria, A., Vladis, N. A., Risse, B., Mangan, M., & Webb, B. 2019, August. Robustness of a model of the insects' celestial compass in realistic conditions. In International Conference on Invertebrate Vision, Bäckaskog Slott, Sweden.
Gkanias, E., Lagogiannis, K., and Webb, B. 2018, October. Imitating the Drosophila Larval Learning Behaviour on a Robot. In Behavioral Neurogenetics of Drosophila Larva. Edinburgh, United Kingdom.
Pacella, D., Risse, B., Gkanias, E., Mangan, M., and Webb, B. 2018, July. Neural models of ant navigation in a realistic 3D world. In International Conference of Neuroethology. Brisbane, Australia.
List of publications:
Schwarz, S., Clement, L., Gkanias, E., & Wystrach, A. (2020). How do backward-walking ants (Cataglyphis velox) cope with navigational uncertainty?. Animal Behaviour, 164, 133-142.
Gkanias, E., Risse, B., Mangan, M. and Webb, B., 2019. From skylight input to behavioural output: a computational model of the insect polarised light compass.PLoS Comput Biol 15(7): e1007123.
Stouraitis, T., Gkanias, E., Hemmi, J.M. and Webb, B., 2017, July. Predator Evasion by a Robocrab. In Conference on Biomimetic and Biohybrid Systems (pp. 428-439). Springer, Cham.