Kathryn finished her studies in theoretical physics in 2016 at the University of Sussex, and joined NPL soon after completing her PhD in cold atom trapping. Kathryn originally joined NPL in the time and frequency department but is now a member of the data science department working on autonomous vehicle metrology.
Kathryn’s expertise within the Assured Autonomy team is in mathematical modelling and data analysis. Working collaboratively with colleagues and the MET Office she uses traditional and data driven modelling to realistically model and understand how situational awareness sensors used for autonomous navigation may be affected by weather conditions. Kathryn also works on Virtual Test Environment (VTE) Assurance, working on developing strategies to have confidence in safety testing carried out in virtual AV simulators and maximise the impact that virtual testing can bring.
Kathryn has a passion for outreach and knowledge transfer, she has previously worked collaboratively with the NPL Training team to develop training resources on clock statistics.
Areas of interest
• Assured autonomy – traceability and trustworthiness for autonomous vehicle sensors and systems
• Validation, Verification and Assurance testing of VTE Simulators
• Mathematical modelling of applied physical systems and fundamental physics experiments
• Atomic physics, particularly in uncertainty calibrations for atomic clocks
• Learning pathways for knowledge transfer and upskilling of scientists in academia and industry