Speakers
Aoibheann Brady (Cervest)
Aoibheann is a Senior Statistical Scientist developing models that feed the signals used in Cervest’s climate intelligence product, EarthScan. She is particularly interested in understanding how environmental exposures vary in space and time, and how we can use our understanding of spatial proximity to inform and enhance Cervest’s modeling of climate hazard exposure risk. She did her PhD at Bath.
Tatiana Kim (Napster)
Tatiana is a Senior Data Scientist responsible for algorithmic delivery of genre specific music charts in over 50 territories as well as designing and building a new recommendation system in GCP for Napster, a music streaming company based in the USA. She did her BSc, MSc and PhD all at Bath.
Alice Davis (Mayden)
Alice is a Health Data Scientist at Mayden, based in Oldfield Park. Through her statistical analysis of electronic health records, Alice is aiming to statistically model patient engagement in psychological therapy (IAPT services) which deliver talking therapies such as cognitive behavioural therapy. She did her undergraduate and PhD at Bath, and initially joined Mayden as a Knowledge Transfer Partnership (KTP) Associate.
Katie Thorn (GSK)
Katie is Advanced Analytics Modelling Lead at GSK. She did her BSc at Bath, spending a year doing a placement in the pharmaceutical industry. She is a member of the PSI CALC committee which aims to promote and raise awareness of careers in medical statistics to students of all ages.
Tatiana Bubba
Tatiana is a Lecturer in the Department, whose research interests lie at the interface of mathematical sciences and imaging. She studies non-smooth regularisation approaches, convex optimisation methods and machine learning techniques for image analysis and inverse problems, among them image reconstruction, for static and dynamic targets, image classification and segmentation.
Ilaria Bussoli
Ilaria is a Lecturer in the Department, working on statistics. Her speciality is graphical probabilistic modelling, focusing on conditional Gaussian graphical models. She is particularly enthusiastic about the public understanding of statistics.
Clarice Poon
Clarice is a Lecturer in the Department, and her research is in inverse problems, with a particular interest in how one can exploit the structural properties of the underlying data for the purpose of efficient data sampling and optimisation schemes.
If you have any questions about the event please get in touch with one of the organisers, Merisse Baker or Inés Blanco.