Offline Deep Reinforcement Learning for Dynamic Pricing of Consumer Credit. - Raad Khraishi; Ramin Okhrati (ICAIF, 2022)

Eigenvector-based Graph Neural Network Embeddings and Trust Rating Prediction in Bitcoin Networks. - Pin Ni; Qiao Yuan; Raad Khraishi; Ramin Okhrati; Aldo Lipani; Francesca Medda (ICAIF, 2022)

An Introduction to Machine Unlearning. - Salvatore Mercuri; Raad Khraishi; Ramin Okhrati; Devesh Batra; Conor Hamill; Taha Ghasempour; Andrew Nowlan (CoRR, 2022)

Modelling customer lifetime-value in the retail banking industry. - Greig A. Cowan; Salvatore Mercuri; Raad Khraishi (CoRR, 2023)

Simple Noisy Environment Augmentation for Reinforcement Learning. - Raad Khraishi; Ramin Okhrati (CoRR, 2023)

Conformal Predictions for Longitudinal Data. - Devesh Batra; Salvatore Mercuri; Raad Khraishi (CoRR, 2023)

Agent-based Modelling of Credit Card Promotions. - Conor B. Hamill; Raad Khraishi; Simona Gherghel; Jerrard Lawrence; Salvatore Mercuri; Ramin Okhrati; Greig A. Cowan (CoRR, 2023)

How Personality Traits Shape LLM Risk-Taking Behaviour. - John Hartley; Conor Brian Hamill; Dale Seddon; Devesh Batra; Ramin Okhrati; Raad Khraishi (ACL (Findings), 2025)

Evaluating the Sensitivity of LLMs to Prior Context. - Robert Hankache; Kingsley Nketia Acheampong; Liang Song; Marek Brynda; Raad Khraishi; Greig A. Cowan (CoRR, 2025)

Obscured but Not Erased: Evaluating Nationality Bias in LLMs via Name-Based Bias Benchmarks. - Giulio Pelosio; Devesh Batra; Noémie Bovey; Robert Hankache; Cristovao Iglesias; Greig A. Cowan; Raad Khraishi (CoRR, 2025)