Yazan Qarout (Aston, 2018-)

Yazan is developing novel signal processing algorithms for understanding and quantifying unconstrained human behaviours from sensor data.

Adam Farooq (Aston, 2018-)

Adam's primary research is concerned with developing fast nonparametric signal processing algorithms using Bayesian nonparametrics.

Ugur Kayas (Aston, 2018-)

Ugur is investigating the application of abstract algebras to simplify complex machine learning algorithms.

Katy Weihrich (Manchester and Aston, 2017-)

Katy's work is concerned with extracting clinically meaningful information about pain in musculoskeletal diseases from wrist-worn sensor data.

Alex Oldroyd (Manchester and Aston, 2017-)

Alex is investigating the use of wearable devices for the objective characterization of movement impairment in myositis.

Anna Beukenhorst (Manchester and Aston, 2017-)

Anna's work involves processing sensor data from smartwatches to characterize knee pain in osteoarthritis.

Reham Badawy (Aston, 2014-)

Reham has a combined honours background in neuroscience and computer science, and is investigating how to detect and quantify Parkinson's disease prodromally (that is, before the symptoms are readily apparent in clinic), using mass-scale data collected using smartphones.

Jordan Raykov (Aston, 2013-2016)

Jordan's primary research improved the computational tractability of inference in Bayesian nonparametric models such as combinatorial stochastic processes. For example, he developed novel maximum a-posteriori algorithms for Dirichlet process mixtures and infinite HMMs. He is now a Lecturer at Aston University.

Ben Fulcher (Oxford, 2009-2012)

Ben worked on massively systematic approaches to time series analysis. He applied a vast array of analysis algorithms across multidisciplinary time series, discovering empirical structural relationships between seemingly unrelated analysis algorithms and suggesting new analysis methods that cross disciplinary boundaries, among many other innovations. He is now a Lecturer at Sydney University.

Paul Moore (Oxford, 2008-2014)

Paul developed time series analysis methods for characterizing and predicting bipolar disorder, based on a large and unique set of weekly, self-reported symptom data in the form of mobile phone texts. He used methods such as Gaussian process regression and exponential smoothing.

Athanasios Tsanas (Oxford, 2008-2012)

Thanasis' D.Phil. research explored the use of voice recordings to develop objective, automated tools for detecting Parkinson's and predicting symptom severity. Thanasis is currently a Chancellor's Fellow at Edinburgh.