Dr Davide Pigoli
Senior Lecturer in Statistics
Research interests
- Mathematics
Biography
Davide Pigoli received his Ph.D. in Mathematical Models and Methods in Engineering from Politecnico di Milano, Italy, in 2013. His Ph.D. thesis dealt with the statistical inference for covariance operators in functional data analysis and for spatially distributed covariance matrices. He was a Research Fellow in the Department of Statistics of the University of Warwick from February 2013 to March 2014 and a Research Associate in the Department of Pure Mathematics and Mathematical Statistics of the University of Cambridge between April 2014 and August 2017. Davide joined King's College London as Lecturer in Statistics in September 2017.
Research interests
- Functional and high-dimensional data analysis
- Manifold-valued and object-oriented data analysis
- Spatial statistics
- Applications in linguistics, forensics, quantitative genetics and biosciences
Research Profile
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.
News
Audio-based AI unreliable for predicting Covid-19 infection, study finds
Researchers found that technology using Machine Learning performed no better than simply asking people to report their symptoms
Events
Mean-field reinforcement learning
Conference on mean-field games/mean-field type control, machine learning techniques and deep reinforcement learning based algorithms for dynamic optimization...
Please note: this event has passed.
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.
News
Audio-based AI unreliable for predicting Covid-19 infection, study finds
Researchers found that technology using Machine Learning performed no better than simply asking people to report their symptoms
Events
Mean-field reinforcement learning
Conference on mean-field games/mean-field type control, machine learning techniques and deep reinforcement learning based algorithms for dynamic optimization...
Please note: this event has passed.