
Dr Daniel Lawson
MSc(Bristol), PhD(Lond.)
Expertise
Associate Professor of Data Science, working on methods for genetic ancestry estimation, and application of machine learning and AI to a wide range of disciplines. See https://people.maths.bris.ac.uk/~madjl/
Current positions
Associate Professor in Data Science
School of MathematicsInterim Director, University Research Institute
Research, Enterprise and Innovation
Contact
Press and media
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Biography
My research is on applied statistics, particularly pullthrough of interesting methods into consequential applications - recent work has focussed on spectral methods, Graph Neural Networks, conformal inference and Bayesian methodology. Applications span earthquakes, culture, and particularly statistical genetics approaches to population structure and what this can tell us about the function of the genome, and even best practice for breeding.
Research interests
Mathematical techniques
Bayesian modelling
Statistical Genetics
Statistical analysis of Big Data
Statistical methods for intractible models
Dynamical systems and game theory
Networks
Application areas
Genetics
Epidemiology
Historical dynamics
Ecology
Projects and supervisions
Research projects
OCeanic and South East Asian Navigators.
Principal Investigator
Managing organisational unit
School of MathematicsDates
01/01/2020 to 31/12/2023
Thesis supervisions
Measuring the Dynamics of Cultural Values and their Role in Human Development
Supervisors
Hybridisation and introgression in the Scottish wildcat
Supervisors
Enhancing Earthquake Forecasting
Supervisors
Investigating the influence of natural selection on the genetic architecture of molecular traits
Supervisors
Publications
Selected publications
01/01/2012Inference of population structure using dense haplotype data
PLoS Genetics
Recent publications
07/03/2025Assessing geographic polarisation in Britain’s digital landscape through stable dynamic embedding of spatial web data
EPJ Data Science
Continental influx and pervasive matrilocality in Iron Age Britain
Nature
Fine-scale population structure and widespread conservation of genetic effect sizes between human groups across traits
Nature Genetics
Large-scale selection of highly informative microhaplotypes for ancestry inference and population specific informativeness
Forensic Science International: Genetics
Sparse haplotype-based fine-scale local ancestry inference at scale reveals recent selection on immune responses
Nature Communications