Associate Professor of Statistics
Research Interests: My main research interest lies in the development of statistical methodologies for models with intractable likelihood functions or for misspecified models. These methodologies bring ideas from mathematical statistics (e.g. good old exponential families), machine learning (e.g. deep generative models) and physics (e.g. scoring rules probabilistic predictions) together through neural exponential models, generalised likelihood-free Bayesian inference etc. Applications of them made significant breakthroughs in the fields of meteorology and climate science, population genetics, epidemiology, computational biology and engineering sciences. More details about my research can be found here.
Departmental disability coordinator: If you have concerns or questions regarding disability issues or more broadly about well-being, please don't hesitate to get in touch. More information can be found at the well-being support services website.
3rd & 4th year senior tutor: If you are a 3rd or 4th year student in the department and have questions regarding departmental procedure, please get in touch.
Dr. Lorenzo Pacchiardi, "Statistical inference in generative models using scoring rules", (2022, University of Oxford)
Present PhD students
David Huk, University of Warwick, UK
Shreya Sinha Roy, University of Warwick, UK
Francesca Basini, University of Warwick, UK
Yuexuan Wang, University of Linz, Austria
Yuehao Xu, University of Linz, Austria
- (2022-present): Associate professor, Department of statistics, University of Warwick
- (2018-2022): Assistant professor, Department of statistics, University of Warwick
- (2016-2018) Swiss National Science Foundation Fellow, Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland
- (2012-2016) Research Fellow,Finnish Centre of Excellence in Computational Inference Research, Department of Computer Science, Aalto University, Helsinki
- (2008- 2012) PhD in Statistics, Purdue University, USA
- (2006-2008) MStat in Statistics, Indian Statistical Institute, India
- (2003-2006) BStat in Statistics, Indian Statistical Institute, India
- (2020-2022): UKRI-EPSRC, UK, PI at Warwick University, ‘COVID-19: Optimal Lockdown’.
- (2020-2023): ECMWF, PI at Warwick University, ‘Data-driven calibration of stochastic parametrization of IFS
- (2020-2022): NERC, UK, CoI at Warwick University, ‘Statistical inference and uncertainty quantification for complex process-based models using multiple data sets’.
- (2020-2023): EPSRC, UK, CoI at Warwick University, ‘Twenty20 Insight’.
- (2019-2020): Alan Turing Institute, UK, PI at Warwick University ‘Quantifying effects of climate change on extreme weather events via distributional downscaling’.
- (2016-2018): Swiss National Supercomputing Center, Switzerland, PI, ‘Highly Parallel Data Science based on Approximate Bayesian Computation’.
- (2017-2018): Swiss National Supercomputing Center, Switzerland, PI, “Approximate Bayesian Computation using HPC framework for physical parameter estimation of platelets deposition”.
- (2010-2012): Purdue Research Foundation Fellowship, Purdue University, USA, PI at Purdue University, ‘Path
sampling for Bayesian model selection’
Dr. Ritabrata Dutta
Department of Statistics
University of Warwick
Coventry, UK CV4 7AL
Office: MB4.16 Mathematical Science Building
Office hours: Monday (15:30-16:30) and Wednesday (14:30-15:30)