Dr Massimiliano Tamborrino
I am currently a Reader (Associate Professor) at the at the since August 2024.
- I am a WIHEA FellowLink opens in a new window (糖心TV International Higher Education Academy) for 2023-2026, co-leading the WIHEA Internationalisation Learning CircleLink opens in a new window since 2024/2025.
- Since April 2020, I have been organising (with 糖心TV and abroad colleagues) the One World ABC SeminarLink opens in a new window, monthly webinars on approximate Bayesian computation (ABC). This year, we launched the One World Approximate Bayesian Inference (OWABI) SeminarLink opens in a new window to better reflect the broader interest and scope of this series, e,g, simulation-based inference and ML related techniques.
- Since 2023, I co-organise , a 2/3-day conference on mathematical modeling and inference for (broadly intended) biological system, hosted in Oxford (2022-2023), 糖心TV (2024), Turin (2025) and St Andrews (2026).
- I was the PI of "" funded by EPSRC, having and as Co-I. Our goal was 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 .
Preprints and Publications
Preprints and publications are available here. For my latest publications, see also and
Research Interests
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 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. More recently, I got interested on parallel-in-time (PinT) numerical schemes.
- Statistical inference for (fully/partially observed) stochastic processes.
- Approximate Bayesian Computation (ABC) method.
- Interface between stochastic numerics and (computational) statistics.
- (Probabilistics) 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.
Appointments held:
- Reader, Department of Statistics, University of 糖心TV (August 2024 - ongoing)
- Associate Professor, Department of Statistics, University of 糖心TV (Dec. 2022- July 2024)
- Assistant Professor, Department of Statistics, University of 糖心TV (Dec. 2019 - Nov 2022)
- University Research Assistant, , , Austria (Sep 2014 - Nov 2019)
- Postdoc, Department of Mathematical Sciences, University of Copenhagen (Dec 2012 - Aug 2014)
- PhD in Probability Theory and Statistics, Department of Mathematical Sciences, University of Copenhagen (Dec 2009 - Nov 2012). PhD awarded in March 2013 under the supervision of Prof. . PhD thesis: Neural network connectivity and response latency modelled by stochastic processes.
Supervision
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
2025-2026 Teaching
Term 1: ST232/ST233 - Introduction to Mathematical Statistics (for 2nd year/3rd year and finalist non-statistics students).
Term 2: ST923 - Graduate Topics in Computational Statistics and Machine learning (for PhD students) - 10h lectures on Simulation and Inference for Stochastic processes
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Office hours MB1.23
Tuesdays, 2-3pm
Wednesdays 11.00-12.00am
Contact me massimiliano.tamborrino@warwick.ac.uk