Jonathan Hind is a Senior Research Software Engineer at the CAMHS Digital Lab, King's College London, where he has worked since April 2021. He specialises in machine learning engineering, MLOps infrastructure, and AI applications for paediatric mental health.His work includes building classification models for ADHD and sleep disorders using wearable device data, architecting scalable ML platforms, and developing LLM-powered tools for regulatory processes. He led an infrastructure rebuild that scaled the lab's platform from 5,000 to over 100,000 users and created automation tools saving more than £1.3M in operational costs.Before joining King's, Jonathan co-founded Synthetig, a startup focused on synthetic data generation for privacy-preserving ML, and worked as an ML Engineer at BenevolentAI on drug discovery models. He holds an MSc in Machine Learning and a BSc in Physics, both from Queen Mary, University of London.

Research Interests

• Machine learning for paediatric mental health diagnosis
• Wearable and actigraphy data analysis
• MLOps and scalable ML infrastructure
• LLM development and prompt engineering
• Synthetic data generation for privacy-preserving ML