Implementing knowledge graphs and LLMs in Python to summarize information about data connections, helping to improve information access for non-technical stakeholders at the Home Office.

Highly competitive data science and AI fellowship, providing intensive technical and commercial training, while working on a data science project that has real-world impact. Individually managed and ran a data science project to deliver impact in the health care sector, and presented my results to ~100 guests.

I worked with NHS BNSSG during my fellowship to conceptualise, develop and implement time-series models to predict severe pressure at a system level. To do this I created a Early Warning System tool using forecast models in Python to evaluate when the system is likely to reach high levels of pressure and determine what are the most predictive features of this outcome. I successfully communicated progress reports and results to different stakeholders across the organisation, providing insights from my tool that demonstrate a foundation for mitigating organisational pressures and enhancing operational efficiency.

Conducted research on the cognitive and neural underpinnings of perception (e.g. across sensory modalities). Designed and implemented experimental studies for hypothesis testing in conjunction with fMRI measurements. Executed several quantitative analysis techniques for data analysis such as human behavioral modelling and machine learning (SVMs, RSA) to decode object representations across the brain, using Python and Matlab libraries/packages.

Examined the role of prediction on our perceptual experiences using behavioural and neuroscientific experimental methods including psychophysics and fMRI. Coded tasks and conducted data analysis using MATLAB, Python, Jasp and SPSS. Used a combination behavioural modelling and machine learning analysis techniques.Teaching roles:- Research Methods (statistics) demonstrator- Research Methods in Practice (statistics) demonstrator- Individual mentoring of students in the lab

Continued work on the FAIR data assessment tool project.New project which involved creating a DataTags system based on European laws, specifically the GDPR (General Data Protection Regulation), in which users (researchers) can receive a recommendation on the level of privacy protection their personal data need.

Worked on a project which involved implementing the FAIR principles for high quality Data Stewardship into an online tool which assessed the quality of datasets from different disciplines. This included creating documentation and working on theoretical aspects of our FAIR implementation, designing mockups for our website, creating decision trees for the tool and integrating these into an online survey, conducting and organising internal and external review processes, and giving presentations to varying audiences on the progress of the project.

Received a research bursary to conduct research with Dr Paul Goddard at the University of Lincoln on the phenomenon of the Necker Cube. We examined the various different percepts of the illusion, and analysed and coded data to fit gamma distributions to show the frequencies of time durations for each percept.