Raad K
Data scientist, economist, and programmer
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Based in London, I'm Head of AI R&D at NatWest Group and a PhD candidate at UCL's Institute of Finance & Technology.
Education
- PhD in Finance & Machine Learning, University College London (UCL)
- MSc in Economics, University College London (UCL)
- BA in Economics, University of California, Santa Barbara (UCSB)
- Deep Learning Nanodegree, Udacity
- L3 Personal Trainer, YMCA
- L2 Day Skipper, RYA
Research
Obscured but Not Erased: Evaluating Nationality Bias in LLMs via Name-Based Bias Benchmarks
arXiv Preprint
Giulio Pelosio, Devesh Batra, Noémie Bovey, Robert Hankache, Cristovao Iglesias, Greig Cowan, Raad Khraishi
Evaluating the Sensitivity of LLMs to Prior Context
arXiv Preprint
Robert Hankache, Kingsley Nketia Acheampong, Liang Song, Marek Brynda, Raad Khraishi, Greig A. Cowan
How Personality Traits Shape LLM Risk-Taking Behaviour
Findings of the Association for Computational Linguistics: ACL 2025
John Hartley, Conor Hamill, Devesh Batra, Dale Seddon, Ramin Okhrati, Raad Khraishi
Agent-based Modelling of Credit Card Promotions
International Journal of Bank Marketing
Conor B. Hamill, Raad Khraishi, Simona Gherghel, Jerrard Lawrence, Salvatore Mercuri, Ramin Okhrati, Greig A. Cowan
Conformal Predictions for Longitudinal Data
arXiv Preprint
Devesh Batra, Salvatore Mercuri, Raad Khraishi
Simple Noisy Environment Augmentation for Reinforcement Learning
arXiv Preprint
Raad Khraishi, Ramin Okhrati
Modelling Customer Lifetime Value in the Retail Banking Industry
arXiv Preprint
Greig Cowan, Salvatore Mercuri, Raad Khraishi
An Introduction to Machine Unlearning
arXiv Preprint
Salvatore Mercuri, Raad Khraishi, Ramin Okhrati, Devesh Batra, Conor Hamill, Taha Ghasempour, Andrew Nowlan
Offline Deep Reinforcement Learning for Dynamic Pricing of Consumer Credit
3rd ACM International Conference on AI in Finance (ICAIF ’22)
Raad Khraishi, Ramin Okhrati
Eigenvector-based Graph Neural Network Embeddings and Trust Rating Prediction in Bitcoin Networks
3rd ACM International Conference on AI in Finance (ICAIF ’22)
Pin Ni, Qiao Yuan, Raad Khraishi, Ramin Okhrati, Aldo Lipani, Francesca Medda
Interests
- Reinforcement learning
- Deep learning
- Anomaly detection
- Forecasting
- Economics
- Pricing
- Banking & Finance
Skills
- Programming: Python, Bash, R, Git, HTML, JavaScript, Django, Flask, Stata, MATLAB
- Data Science: PyTorch, PySpark, TensorFlow, Keras, Neo4j, Time-series Forecasting,
Anomaly Detection, Panel Data Analysis, Reinforcement Learning, LLMs
- Other: Calisthenics, Sailing, Hiking, Saxophone, Nay
Toy projects
(no affiliation with my employer)
Contact
If you'd like to reach out, feel free to email me at raadk [at] protonmail [dot] com.