Neil Lawrence
The DeepMind Professor of Machine Learning
Works on uncertainty in machine learning, including Gaussian process methods, and on data governance and the societal impact of AI.
Neil Lawrence's lab at Cambridge works on probabilistic & causal inference and social computing & responsible AI. 12 papers since 2023. 6 PhD students. 13 alumni. Applications close .
At a glance
- papers, 2023–2026
- 3/ year
- at T1 venues
- 0%
- PhD students
- 6
- MS students
- 0
- alumni listed
- 13
Papers by yearfrom the lab homepage, 2023–2026
- 1 papers2026 · T1 0 · collecting
- 2 papers2025 · T1 0
- 6 papers2024 · T1 0
- 3 papers2023 · T1 0
T1 venuesOther
Research focuspaper titles that use each topic's words
- Probabilistic & causal inference3 papers
- Social computing & responsible AI1 paper
- data governance0 papers
- societal0 papers
- governance0 papers
Paper list
From the lab homepage.
20261 paper
- Science and Public PolicyMind the gap: connecting AI innovation to widespread public value
20252 papers
- Third International Workshop on Large Language Models for CodeCode Roulette: How Prompt Variability Affects LLM Code Generation
- ACM Computing SurveysMachine Learning Systems: A Survey from a Data-Oriented Perspective
20246 papers
- Royal Society Open ScienceAccelerating AI for science: open data science for science
- Proceedings of the IEEE/ACM International Conference on AI EngineeringCan causality accelerate experimentation in software systems?
- Data & PolicyIncreasing data sharing and use for social good: Lessons from Africa’s data-sharing practices during the COVID-19 response
- ACM Transactions on Software Engineering and MethodologyRequirements are All You Need: The Final Frontier for End-User Software Engineering
- Proceedings of the International Workshop on New Trends in Software EngineeringSelf-sustaining software systems (S4): Towards improved interpretability and adaptation
- HICSS-58The Systems Engineering Approach in Times of Large Language Models
20233 papers
- Workshop on Bias and Fairness in AI (BIAS), ECMLAutomated discovery of trade-off between utility, privacy and fairness in machine learning models
- EuroMLSysCausal fault localisation in dataflow systems
- IEEE/ACM International Conference on AI Engineering-Software Engineering ApproachesDataflow graphs as complete causal graphs
Where alumni went13 listed
Apply to CambridgeMichaelmas 2027
PhD in Computer Science
- Round
- Funding round (8 Dec 2026)
- Opens
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Confirmed on the program page.
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