Probabilistic Machine Learning and Decision Making

Lead Research Organisation: University of Cambridge
Department Name: Engineering

Abstract

The next wave of automation in machines and services will consist of autonomous systems that are able to make their own decisions. The ability of such systems to learn from data enables them to cope with situations which were not explicitly predicted at the design stage. The decision making should be a process internal to the learning system, as future data collection and potentials are governed partially by current decisions. In this project we will study inference in models of complex non-linear dynamical systems and rational decision making using modern probabilistic methods like Bayesian probability theory. We will study decision support or autonomous systems that are scalable, flexible and learning and explore their application in the domains of IoT, smart cities and digital health.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R511870/1 01/10/2017 30/09/2022
1950384 Studentship EP/R511870/1 01/10/2017 30/09/2021 Robert Pinsler