Senior Data Scientist
Lora has a first degree in Economics and Statistics from UCL. She specialized in Data Science by attaining her MSc in Data Science from LSE in 2020.
Lora joined HDI as an intern in 2018 while at UCL and continued to work while studying at LSE. She has experience and keen interest in advanced machine learning and AI methods. She has explored and optimized their applications to privacy preserving data synthesis and prediction of human behaviour from complex longitudinal data.
During her time as an intern at HDI, Lora improved methodologies for creating the Simulacrum, the synthetic data set derived from cancer patient data. Besides technical work, she has provided guidelines (white papers) and held workshops for practitioners to learn about Simulacrum methodology and the scope of its applications. Lora’s current work focuses on developing deep learning methods to generate synthetic Patient Pathway Data.
On the personal side, Lora is avid traveller, interested in socio-economic and language aspects of different cultures. In her gap year she spent 6 months travelling in South America. Besides English, she speaks Spanish and Serbo-Croatian.
Education and Awards:
2015-2018, BSc Economics and Statistics, UCL
2019-2020, MSc Data Science, LSE
- HDR UK Synthetic Data workshop, 22nd June 2022
- DEDS School – Athens (athenarc.gr), 6th April 2022
- Pie & AI: Aarhus – Synthetic data for health research, 14th March 2022
Talk by Lora on Simulacrum.
- Sharing Synthetic Healthcare Datasets to support Cancer Research:
Lora Frayling speaking at the HDR UK Synthetic Data Special Interest Group, December 2020.
Real-world evidence for patient outcomes and mutational burden in non-small cell lung (NSCLC) cancer patients in England using EGFR biomarker test data from routine clinical care
Real-world outcomes and biomarker testing in cancer patients: exploration of a novel genetic database from routine clinical practice in England
An overview on synthetic administrative data for research