Dr Melanie Stefan is an Edinburgh-Zhejiang Lecturer at the School of Biomedical Sciences at the University of Edinburgh.
In recent years, exciting new opportunities have opened in the study of computational learning and memory — from how neuronal proteins interact and are regulated, to the use of information from educational tools to understand how computers can help people learn.
USING COMPUTATIONAL TOOLS TO UNDERSTAND LEARNING AND MEMORY
My research interests revolve around using computational tools to understand various aspects of learning and memory.
When we learn something, connections between neurons in our brain grow stronger. A complex apparatus — comprised of molecules — found inside a neuron, mediates this process. This machinery receives and transmits signals, which sets in motion a series of functional and structural changes. I work on understanding how these molecules work together and regulate each other.
To do this, I build computer models of neuronal compartments and of the molecules within them. I then run computer simulations of how they react to specific events, such as the activation of a neuronal connection. These simulations help us understand how these systems work, how they are affected by neurological disorders and what effect specific drugs are likely to have. Close collaboration with experimental scientists is crucial in order to test and refine our models and in order to help them make sense of their data.
I am also interested in using computational methods to analyse data from online learning tools. The goal here is to understand how people interact with electronic learning tools and to use this knowledge to support their learning.