PhD in Computing Science - Optimal mechanism design and active inference for advanced human-computer interfaces to machine learning

This project will look at developing “mediating mechanisms” as a way to link machine learning to human-computer interaction in tightly-coupled control loops. The PhD will involve exploring the use of dynamical systems, unsupervised learning/low-dimensional embeddings and probabilistic inference to build robust controls for modern user interfaces. This, for example, might involve mapping of optical hand tracking, pressure sensing or EMG input to machine learning-based recommendation systems – but the PhD would focus on general interaction principles rather than a specific use case. This project is part of a wider ERC project, DIFAI, looking at Active Inference as a principle for human-computer interaction. This project will involve:

(a)    Developing theoretical models of closed-loop interaction from an active inference perspective;

(b)    Designing and implementing mediating mechanisms to link humans to machine learned systems;

(c)    Evaluating the performance and efficacy of the mechanisms through empirical trials.

The PhD will thus involve a mix of experimental work with human subjects, mathematical modelling and implementation of new user interface components.

The successful candidate will have a strong interest/background in human-computer interaction and user modelling as well as a strong background probabilistic modelling, dynamical systems/control theory or active inference and the free energy principle. Strong modelling and software development skills are essential for this studentship.

This PhD project will be part of the ERC Advanced Grant “Designing Freedom through Active Inference (DIFAI)” (funded by the UKRI guarantee scheme).  The candidate would be expected to work within the DIFAI project team.

How to Apply: Please refer to the following website for details on how to apply:

http://www.gla.ac.uk/research/opportunities/howtoapplyforaresearchdegree/.