Dr Caroline Shenton-Taylor
About
Biography
In May 2017 Caroline joined the University of Surrey as an Applied Nuclear Physics Lecturer. Presently her interests include AI and smart data analytics, addressing challenges within nuclear security, nuclear decommissioning, dosimetry, radiation in the environment. medical physics and risk management. Alongside her research and teaching, Caroline is passionate about scientific exchange and runs the YouTube channel Dr CST She is the Season 2 Surrey Speaks Podcast presenter, and has contributed to Radio 4, local radio and numerous festival and outreach events. Explore more of Caroline's outreach work on her Dr CST website.
Caroline obtained her PhD in the field of Magnetic Compton Scattering in 2007 from the University of Warwick. Working with synchrotron X-rays, she explored a range of magnetic materials with applications including enhanced computer memory and innovative refrigeration. From 2007 to 2017 Caroline transitioned into industry, leading a diverse portfolio of scientific research projects on behalf of the UK Ministry of Defence and UK Home Office. Throughout this time Caroline was the Team and Technical Lead for an interdisciplinary research team, focused on the development of novel methods to detect the presence of illegal radiological and nuclear materials.
Caroline was the winner of the 2014 UK Famelab competition and the following year used the prize money to launch a space balloon in honour of Auguste Piccard!
Areas of specialism
University roles and responsibilities
- Physics Undergraduate Admissions Tutor
- Institute of Physics IOP Mentor
My qualifications
Previous roles
News
In the media
ResearchResearch interests
AI & Advanced Data Analytics applied to Nuclear and Medical physics
Current and past projects include:
- Neural networks applied to nuclear decommissioning and medical imaging
- Optimised scintillator section through Fuzzy Logic
- Quantum dot enhanced detection technology
- Wavelet assisted sparse isotope identification
- Risk management through data fusion (nuclear and equestrian sport)
- Novel algorithms and data handling applied to radiation spectra
- Optimised sensor placement for radiological research
- Innovative alpha detection for environmental applications
Research collaborations
Caroline has collaborated and exchanged scientific ideas with a wide range of organisations including:
- US Government Defence Departments
- US National Laboratories
- University of Illinois
- AWE
- BAE
- Imperial College London
- University of Manchester
- University of Liverpool
- University College London
- St Mary's University
- National Nuclear Laboratory
- National Physical Laboratory
- Royal Surrey NHS Foundation Trust
- UK Home Office
- UK Ministry of Defence.
Research interests
AI & Advanced Data Analytics applied to Nuclear and Medical physics
Current and past projects include:
- Neural networks applied to nuclear decommissioning and medical imaging
- Optimised scintillator section through Fuzzy Logic
- Quantum dot enhanced detection technology
- Wavelet assisted sparse isotope identification
- Risk management through data fusion (nuclear and equestrian sport)
- Novel algorithms and data handling applied to radiation spectra
- Optimised sensor placement for radiological research
- Innovative alpha detection for environmental applications
Research collaborations
Caroline has collaborated and exchanged scientific ideas with a wide range of organisations including:
- US Government Defence Departments
- US National Laboratories
- University of Illinois
- AWE
- BAE
- Imperial College London
- University of Manchester
- University of Liverpool
- University College London
- St Mary's University
- National Nuclear Laboratory
- National Physical Laboratory
- Royal Surrey NHS Foundation Trust
- UK Home Office
- UK Ministry of Defence.
Supervision
Postgraduate research supervision
Current PhD students within the Nuclear AI Team, by starting year
- Machine Learning Techniques Applied to Challenging Gamma Spectra (2019)
- Development and use of new and derived data to facilitate the optimisation and evaluation of breast screening AI tools (2022)
- Assessing the reliability of AI for predicting the risk of breast cancer (2022)
PhD alumni, by graduation year
- Silica based fibres for radiation dosimetry, C Termsuk (2022)
- Quantum Dot Loaded Nanocomposite Plastic Scintillators, C. Grove (2021)
- Thermoluminescence of silica beads for dosimetry up to 250 kGy, K. Ley (2020) formerly with Dr Lohstroh
General topics for future UG, MSc and PhD projects
- Fuzzy logic for nuclear applications
- Convolutional neutral networks applied to Nuclear Security
- Machine leaning within Nuclear Medicine
- Use of automatic AI code generation for the Nuclear Industry
- AI Deep Learning methods
- Genetic algorithms, sparse data techniques
Teaching
Current Teaching, Semester 1
- U/G Year 1 (Level 4) PHY1033, Fundamentals of Physics
- U/G Year 1 (Level 4) Small Group Tutorial Classes
- MSc Radiation Laboratory (Level 7) PHYM054 & PHYM036, part of academic supervisory team
Current Teaching, Semester 2
- U/G Year 3 (Level 6) PHY3063 STEM Education and Public Engagement
- MSc Extended Group (Level 7) PHYM041
Supervisions
- PhD supervision
- MSc Dissertation Project supervision
- MPhys Visiting Tutor
- BSc Final Year Project supervision
- Professional Training Year (PTY) Visiting Tutor
- Personal Tutor
Publications
Highlights
Examples of co-authored publications/articles/proceedings are listed below.