I am an Associate Professor at the Department of Statistics at the University of Warwick since December 2022 (and Assistant professor before, December 2019 - November 2022). I am also WIHEA FellowLink opens in a new window (Warwick International Higher Education Academy), 2023-2026. Before moving to Warwick, I was a University Research Assistant at the Institute for Stochastics, JKU Linz, Austria (2014-2019) and Postdoc at the Department of Mathematical Sciences, University of Copenhagen, where I obtained my PhD in Probability Theory and Statistics under the supervision of Professor Susanne Ditlevsen in 2013.
- I'm PI of "AI-informed decision making based on decision field theoryLink opens in a new window" funded by EPSRC, having Lyudmila GrigoryevaLink opens in a new window and Shweta SinghLink opens in a new window as Co-I. Our goal is to perform AI-informed decision making driven by Decision Field Theory (DFT), proposing a new set of what we call AI-informed DFT-driven decision-making models. Such models integrate human behaviour with AI by combining stochastic processes coming from DFT with ML tools and have the unique feature of having interpretable parameters. A broad summary can be found hereLink opens in a new window. Get in touch if you're interesting in becoming involved.
- Together with other colleagues from Warwick and abroad, I am organising the One World ABC SeminarLink opens in a new window, monthly seminar series on approximate Bayesian computation (ABC) and approximate Bayesian inference.
Preprints and Publications
My interest is in the study of stochastic processes (mostly diffusions) and point processes from a modelling, numerical, probabilistic and statistical point of view. In particular, I am currently interested in the interface between numerics and statistics when considering simulation-based methods applied to problems arising mainly, but not exclusively, in neuroscience, physiology, cognitive psychology and biology.
- Statistical inference for (fully/partially observed) stochastic processes.
- Approximate Bayesian Computation (ABC) method.
- Interface between stochastic numerics and (computational) statistics.
- Parallel-in-time (PinT) numerical schemes.
- Stochastic modelling in neuroscience.
- Mathematical and computational neuroscience
- Hitting times (also known as first passage times).
- Statistical inference for point processes.
- Dependence measures between point processes.
Students interested in working in one of the above topics are encouraged to contact me. A list of possible PhD projects and ongoing/supervised PhD projects, BSc and MSc dissertations is available here.Link opens in a new window