I am interested in machine learning in general, its interplay with mathematics and statistics and its applications. In particular, my research interests include probabilistic models, kernel methods, and stochastic processes. I work on the development of new probabilistic models and their application in different engineering and scientific areas that include Neuroscience, Neural Engineering, Systems biology, and Humanoid Robotics.
There are two PhD positions in my group:
Identifying determinants of co-morbidities in patients affected by osteoarthritis using machine learning. Applications close on May 1, 2020. Dr Maria-Cruz Villa is the main supervisor. I am a co-supervisor on this one.
Deep Probabilistic Models for resolution enhancement of diffusion magnetic resonance imaging Applications close on May 22, 2020. Co-supervised with Dr Paul Armitage (from Academic Radiology at Sheffield).
We are looking for candidates with a strong mathematical and computational background. For informal enquiries, you can email me at: myfirstname dot myfirstsurname at sheffield dot ac dot uk.
Accepted paper at AISTATS 2020, Black-box Inference for Non-linear Latent Force Models, with Wil Ward, Tom Ryder and Dennis Prangle.
New preprint, A Fully Natural Gradient Scheme for Improving Inference of the Heterogeneous Multi-Output Gaussian Process Model with Juan-José Giraldo.
New preprint, Continual Multi-task Gaussian Processes, with Pablo Moreno-Muñoz and Antonio Artés-Rodríguez.