James A. Grant

Dr James A. Grant is a Lecturer in Statistics at the School of Mathematical Sciences, Lancaster University, with affiliations at Fylde College. He earned his PhD through the STOR-i Centre for Doctoral Training in 2019.

• Current Postgraduate Supervision
• Active Industry Collaborations (BT, Tesco, Datasparq)
• Research Specializations: Bandit Learning, Reinforcement Learning, Algorithm Design

His research focuses on bandit learning and reinforcement learning algorithms that optimize decision-making through iterative model updates. Key themes include:

• Handling complex data and models
• Multi-fidelity simulation networks
• Safety constraints in reinforcement learning
• Streaming data applications
• Phylogenetic tree analysis
• Federated learning architectures

Recent work trends show emphasis on:

• Contextual bandit frameworks
• Interdisciplinary applications (biology, digital infrastructure)
• Industry-partnered projects
• Personalization in algorithm design
• Statistical convergence guarantees
• Simulation optimization techniques

Grant currently supervises 5 PhD students across diverse topics including:

• Triggered bandits in streaming data
• Multi-fidelity modeling
• Safety mechanisms in reinforcement learning