Dr James Cussens
BSc, PhD
Expertise
I work in machine learning (ML), mainly learning Bayesian networks from data. Bayesian networks represent relationships between variables and can (sometimes) be used to represent causal relations. I also work on ML using logic.
Current positions
Senior Lecturer
School of Computer Science
Contact
Press and media
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Projects and supervisions
Research projects
Code Encounters: Algorithmic risk profiling tools as housing market intermediaries
Principal Investigator
Role
Co-Investigator
Managing organisational unit
School for Policy StudiesDates
01/01/2022 to 31/12/2023
Tailoring health policies to improve outcomes using machine learning, causal inference and operations research methods
Principal Investigator
Managing organisational unit
Department of Computer ScienceDates
01/09/2020 to 31/08/2023
Tailoring health policies to improve outcomes using machine learning, causal inference and operations research methods
Principal Investigator
Managing organisational unit
Department of Computer ScienceDates
01/09/2020 to 31/08/2023
Tailoring health policies to improve outcomes using machine learning, causal inference and operations research methods
Principal Investigator
Managing organisational unit
School of Computer ScienceDates
01/09/2020 to 31/08/2023
Publications
Recent publications
27/01/2025Algorithmic tenancies and the ordinal tenant
Housing Studies
Open Banking and data reassurance: the case of tenant referencing in the UK
Information, Communication & Society
Valuing the manual
Social and Cultural Geography
Algorithmic dwelling? Digital technologies as intermediaries in housing access and the enactment of home
Information, Communication & Society
Branch-Price-and-Cut for Causal Discovery
Proceedings of Machine Learning Research (PMLR)
Teaching
I teach machine learning, currently the 3rd year unit on machine learning, and also Applied Data Science.
