The Organ that Studies Itself: A Computational Perspective of the Brain

Thursday 22 November 2018, 6.00pm for presentation starting at 6.30pm, following a brief BCS eLearning SG AGM

Southampton Solent University, East Park Terrace, Southampton, SO14 0RD

In TS103, in The Spark Building (on East Park Terrace, adjacent and north to the Library). (This is about 10 minutes’ walk from the Southampton Central Station).
Room TS103 is on the first floor in the Spark building, behind the Reception. Directions and maps

Parking is available after 4.30pm in the staff car park from the entrance in Andrews Road, on your left as you approach the Jurys Inn.  

Note the external doors might be closed at 6.00pm, so if you cannot get in after 6.00pm, a special phone will be switched on from 6.00pm to 7.00pm only - number sent to those that have booked

Cost: Free and open to both BCS and Non-BCS Members.

This is a joint event with the BCS Hampshire Branch, BCSWomen, BCS e-Learning SGs and Solent University, Computing Subject Group Research Seminar.


The human brain has often been described as the most complex structure in the known universe. Today the field of neuroscience combines theoretical and experimental approaches with computational modelling to study the properties of the nervous system at different levels - from molecules to the circuits of neurons that enable behaviour. The simulation of such models is achieved through powerful computational neuronal simulation environments.

Carrying those large-scale presents unique computational challenges in terms of extensibility, scalability, and computational efficiency as well as insights for the field of machine learning.

This talk describes novel implementations to the simulation of neural systems and their importance in the field and presents a different path for neural simulations.

Dr. Kristina KapanovaAssistant Professor Kristina Kapanova, PhD has obtained her PhD in 2017 on developing new algorithms for the training and design of artificial neural networks. She has also worked with prof. Sellier on the application of his signed-particle formulation of quantum mechanics to time-dependent, single - and many-body, multi-dimensional quantum problems related to various disciplines. Currently, Kristina focuses on new algorithms for the computation of biological neural networks and their practical implementation.

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