Dr Marina Riabiz
Lecturer in Statistics
- DT4Health Co-Lead (Recruitment and Mentoring)
Research interests
- Mathematics
Contact details
Biography
Marina Riabiz received her undergraduate and master’s degree in Mathematical Engineering from Politecnico di Milano, Italy, specialising in Applied Statistics. She completed her PhD in the Signal Processing Group, Information Engineering, at the University of Cambridge, UK, working on latent variable models for Bayesian inference with stable distribution and processes. She joined King’s College London in 2018 as a postdoctoral researcher in the Cardiac Electro-Mechanics Research Group (BMEIS), working on uncertainty quantification for cardiac myocyte models. During this time, she was also a visiting researcher at the Alan Turing Institute. In September 2021 Marina joined the Department of Mathematics as a Lecturer in Statistics.
Research interests
- Computational statistics
- Probabilistic machine learning
- Bayesian inference
- Medical sciences and engineering applications
Further information
Academic co-lead Centre for Doctoral Training DT4Health
NMES representative King’s Institute for Artificial Intelligence
Research
Statistics
The group has research strengths in the design and analysis of experiments, time series and Markov chain Monte Carlo and sequential Monte Carlo methods.
Centre for Doctoral Training in Digital Twins for Healthcare
DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.
DT4Health: Projects
DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.
DT4Health: Research
DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.
DT4Health: Training
DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.
Research
Statistics
The group has research strengths in the design and analysis of experiments, time series and Markov chain Monte Carlo and sequential Monte Carlo methods.
Centre for Doctoral Training in Digital Twins for Healthcare
DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.
DT4Health: Projects
DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.
DT4Health: Research
DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.
DT4Health: Training
DT4Health brings together a world-class multidisciplinary team of supervisors to train future innovation leaders to articulate and materialise the Digital Twin vision in healthcare.