Publications
Publications
A Research Agenda for Data Trusts (Working Paper 3)
The Data Trusts Initiative:
Accelerating AI for science: open data science for science
Royal Society Open Science, 11(8):
Adversarial Concept Erasure in Kernel Space
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The UK Foundation Models Opportunity (AI Council Briefing)
AI Council:
Data Governance in the 21st century: Citizen Dialogue and the Development of Data Trusts
Future Directions for Citizen Science and Public Policy, CSaP:
Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment
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AI for Science: an emerging agenda
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AI for Science: Reframing AI's Role in Discovery
RSS: Data Science and Artificial Intelligence, :
AI Public Dialogues: Understanding Public Perspectives on AI in Government Missions
ai@cam:
An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context
1st International Conference on AI Engineering – Software Engineering for AI, :
Natural Language Processing markers in First Episode Psychosis and People at Clinical High-risk
Translational Psychiatry, 11(630):
Automated discovery of trade-off between utility, privacy and fairness in machine learning models
3rd Workshop on Bias and Fairness in AI (BIAS), ECML 2023, :
Bayesian learning via neural Schrödinger–Föllmer flows
Statistics and Computing, 33(3):
Behavioral experiments for understanding catastrophic forgetting
AI Evaluation Beyond Metrics (EBeM), IJCAI, :
Benchmarking Real-Time Reinforcement Learning
Pre-registration Workshop at NeurIPS 2021, :
Bottom-up Data Trusts: Disturbing the 'One Size Fits All' Approach to Data Governance
International Data Privacy Law, Oxford Academic 9(4):236-252
Can causality accelerate experimentation in software systems?
Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering, :
Causal fault localisation in dataflow systems
Proceedings of the 3rd Workshop on Machine Learning and Systems (EuroMLSys), :
Challenges in Machine Learning Deployment: A Survey of Case Studies
ACM Comput. Surv., Association for Computing Machinery:
Creating a European AI Powerhouse: A Strategic Research Agenda from the European Learning and Intelligent Systems Excellence (ELISE) consortium
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Creating a Pathway to Successful Real-World Data Trusts
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Data trusts: from theory to practice (Working Paper 1)
The Data Trusts Initiative:
Data Trusts: Supporting Trustworthy Data Use
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Dataflow graphs as complete causal graphs
2nd International Conference on AI Engineering – Software Engineering for AI, :
Decision-making with Uncertainty
Significance, 17(6):12-12
Deep learning for Bioimage Analysis in Developmental Biology
Development, 148(18):
Deep Neural Networks as Point Estimates for Deep Gaussian Processes
Advances in Neural Information Processing Systems 34 (NeurIPS 2021), :
Democratising the Digital Revolution: The Role of Data Governance
Reflections on Artificial Intelligence for Humanity, :
Desiderata for next generation of ML model serving
NeurIPS Workshop on Challenges in Deploying and Monitoring Machine Learning Systems (DMML), :
Differentially Private Regression and Classification with Sparse Gaussian Processes
Journal of Machine Learning Research, 22(188):1-41
Dimensionality Reduction as Probabilistic Inference
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Efficient Representations for Privacy-Preserving Inference
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Empirical Bayes Transductive Meta-Learning with Synthetic Gradients
International Conference on Learning Representations, :
Enhancing patient stratification and interpretability through class-contrastive and feature attribution techniques
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Exploring Legal Mechanisms for Data Stewardship
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Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, :
Framework Conditions and Funding for AI in Science: Mutual Learning Exercise on National Policies for AI in Science – First Thematic Report
Publications Office of the European Union:
From Research Data Ethics Principles to Practice: Data Trusts as a Governance Tool
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Gaussian Process Latent Variable Flows for Massively Missing Data
Third Symposium on Advances in Approximate Bayesian Inference, :
iFogSim-Placement: A Simulation Framework for Edge Service Placement
Proceedings of the 21st International Conference on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2026), :253-258
Increasing data sharing and use for social good: Lessons from Africa’s data-sharing practices during the COVID-19 response
Data & Policy, 6:
International Perspectives on the Development of Data Institutions (Working Paper 2)
The Data Trusts Initiative:
Investigating Uncertainty in Postoperative Bleeding Management: Design Principles for Decision Support
Proceedings of the 35th International BCS Human-Computer Interaction Conference (HCI2022), :
Is Embodiment Necessary for Consciousness?
Perspectives on Machine Consciousness, Chapman & Hall:
The UK Large Language Models Opportunity (AI Council Memo)
AI Council:
Letter Warning about Simplistic Narratives around AI
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LLM Performance for Code Generation on Noisy Tasks
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Machine Learning for Science: Mathematics at the Interface of Data-driven and Mechanistic Modelling
Oberwolfach Reports, EMS Press 20(2):
Machine Learning from Innovation to Deployment: A Strategic Research Agenda for AutoAI
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Mind the gap: connecting AI innovation to widespread public value
Science and Public Policy, :
Model Comparison for Semantic Grouping
Proceedings of the 36th International Conference on Machine Learning, :
Modeling the Machine Learning Multiverse
Advances in Neural Information Processing Systems (NeurIPS), :
Modelling Technical and Biological Effects in scRNA-seq Data with Scalable GPLVMs
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Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis
Journal of Machine Learning Research, 22(8):1-51
Multi-fidelity experimental design for ice-sheet simulation
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Multilingual Factor Analysis
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, :
Multimodal Graph Coarsening for Interpretable, MRI-Based Brain Graph Neural Network
IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), :
National Commission into the Regulation of AI in Healthcare: Recommendations for a future regulatory framework
MHRA:
On Feature Learning for Titi Monkey Activity Detection
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Optimal marker gene selection for cell type discrimination in single cell analyses
Nature Communications, 12(1186):
Predicting Ruthenium Catalysed Hydrogenation of Esters Using Machine Learning
Digital Discovery, RSC 2:
Prompt Variability Effects on LLM Code Generation
Third International Workshop on Large Language Models for Code (LLM4Code 2026), co-located with ICSE 2026, :
Public Dialogue on AI in Local Government
ai@cam:
Machine Learning Systems: A Survey from a Data-Oriented Perspective
ACM Computing Surveys, :
Requirements are All You Need: The Final Frontier for End-User Software Engineering
ACM Transactions on Software Engineering and Methodology, :
Scalable Amortized GPLVMs for Single Cell Transcriptomics Data
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Self-sustaining software systems (S4): Towards improved interpretability and adaptation
Proceedings of the 1st International Workshop on New Trends in Software Engineering, :
Shooting Schrödinger's Cat
Fourth Symposium on Advances in Approximate Bayesian Inference, :
Societal Alignment Frameworks Can Improve LLM Alignment
FAccT '26: The 2026 ACM Conference on Fairness, Accountability, and Transparency, :
Solving Schrödinger Bridges via Maximum Likelihood
Entropy, 23(9):1134
Sparse Gaussian Processes with Spherical Harmonic Features
Proceedings of the 37th International Conference on Machine Learning, :
The Atomic Human: Understanding ourselves in the age of AI
Allen Lane:
The Human Visual System Can Inspire New Interaction Paradigms for LLMs
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The Inaccessible Game
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The Origin of the Inaccessible Game
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The No Barber Principle: Towards Formalised Selection in the Inaccessible Game
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The Systems Engineering Approach in Times of Large Language Models
58th Hawaii International Conference on System Sciences (HICSS-58), :
Towards Better Data Discovery and Collection with Flow-Based Programming
Neurips Data-Centric AI Workshop (DCAI), :
Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE
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