Cyndie Demeocq 

Email: C.Demeocq@sms.ed.ac.uk

Research keywords: Generative AI, LLMs, MLLMs, Child Safety, Illegal Harms

Bio:

Cyndie has a background in data science and machine learning with a specific focus on natural language processing (NLP) and multimodal machine learning (MML). She is especially interested in data-driven methods and solutions. She spent several years working for technology and regulatory organisations in France, Sweden, the USA and the UK. Her main interests lie in approaching technology to address illegal activities online and prevention solutions for child safety. In addition to being part of the CDT programme within the University of Edinburgh, her support includes the organisation Childlight as part of their Global Data Fellow programme. 

PhD research:

Her research focuses on approaching the potential opportunities and emerging risks of generative AI models such as large language models (LLMs) and multimodal large language models (MLLMs) for illegal harms, especially those toward children, their applications for law enforcement practitioners, and the development of preventive technological frameworks for industry.

Supervisor: Björn Ross