I have applied experience with developing and applying data science and machine learning solutions, including deep learning and probabilistic modelling, as well as developing and deploying data systems and code. I have acted in a number of teaching and supervisory roles in software, computing and machine learning-related modules and projects.
PhD Computer Science, University of Nottingham, 2018
Thesis title: “Development of machine learning techniques for characterising changes in time-lapse resistivity monitoring”
MSci Mathematics and Computer Science, University of Nottingham, 2013
First class with honours
Teaching Fellow, 2023—present
School of Computing and Mathematical Sciences, University of LeicesterI have joined the school as a teaching fellow, responsible for the undergraduate teaching of Internet and Cloud Computing, project supervision and personal tutoring.
Research Associate in Uncertainty in Infrastructure Systems, 2022—2023
Department of Civil and Structural Engineering, University of SheffieldIn this role, I investigated the limitations of incomplete information and data in large scale systems-of-systems models, and helped develop research proposals to address them.
Research Associate in Data Driven Retrofit, 2020—2022
Department of Civil and Structural Engineering, University of SheffieldThis role involved leading research and development on solutions to large-scale modelling of energy needs for home retrofit, using multiple sources of data including visual and thermal imaging, and open geospatial datasets. In this role, I developed solutions to research questions, managed a large scale data capture and storage project, and led a small team of data scientists to solve data localisation and management challenges. I worked on successful grant proposals and led small technical and research projects.
Research Associate in Physically Informed Machine Learning, 2019—2020
Department of Physics and Astronomy / School of Mathematics and Statistics, University of SheffieldI investigated Bayesian statistics-based methods for inferring nonlinear spatio-temporal dynamics in material physics, combining adjoint methods with optimisation techniques.
Research Associate in Probabilistic Machine Learning, 2017—2019
School of Computer Science, University of SheffieldI worked on the development of deep learning and probabilistic models for non-linear dynamic systems with partial understanding, particularly with the use of Gaussian processes.
Research Programmer (part time), 2017
Department of Mathematical Sciences, Loughborough UniversityI developed and prototyped research software for 4-D medical imaging and visualising advanced statistical analysis for clinical use.
University Teaching Assistant, 2014—2017
School of Computer Science, University of NottinghamLeading development and implementation of practical teaching in undergraduate courses on 3-D graphics, software quality management, and professional ethics in computing.
BUFI Researcher, 2014—2017
British Geological SurveyEmbedded within the Geophysical Tomography team conducting research on computational approaches for analysis in geophysical monitoring.
Impacts of retrofit at scale: analysing the decisions behind retrofit
Principal Investigator
Funder: Centre for Postdoctoral Development in Infrastructure Cities and Energy
Value: £29,996
Digital twins for high-value engineering applications
Named researcher / workpackage lead
Funder: The Alan Turing Institute
Value: £713,107
BGS-University Funding Initiative Scholarship
Recipient
Funder: British Geological Survey
Value: £19,800
School of Computer Science PhD Scholarship
RecipientFunder: EPSRC / University of Nottingham
Guest Editor, Buildings, 2023—present
“Computational Methods in Building Energy Efficiency Research”
Thesis Mentor, 2018-2020
Network Coordinator / Founder, Sheffield Machine Learning Network, 2018—2020
I established a research network dedicated to connecting researchers in the university. My role involved developing and sharing outreach material, and organising events.