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
Dates
01/09/2020 to 31/08/2023
Tailoring health policies to improve outcomes using machine learning, causal inference and operations research methods
Principal Investigator
Dates
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
20/09/2026Algorithmic risk and social housing access in England
Housing and Society
Algorithmic tenancies and the ordinal tenant: digital risk-profiling in England’s private rented sector
Housing Studies
Envisioning Mortgage Futures
Housing, Theory and Society
Learning Bayesian Network Classifiers to Minimize Class Variable Parameters
Journal of Machine Learning Research
Speculating on Speculation? Thinking Within and Beyond the Mortgage Present a Reply to the Comments on ‘Envisioning Mortgage Futures’
Housing, Theory and Society
Teaching
I teach machine learning, currently the 3rd year unit on machine learning, and also Applied Data Science.
