CV
The full version can be downloaded above.
Basics
| Name | Tom Lamb |
| Label | DPhil Candidate in Machine Learning |
| thomas.lamb@eng.ox.ac.uk | |
| Url | https://tomalamb.github.io |
| Summary | AI safety, robustness, and reliable machine learning, with an emphasis on uncertainty quantification and generalisation, particularly in the context of LLMs. My work spans semantic calibration and uncertainty quantification for LLMs; steering LLMs adaptively at inference time; biases in VLMs; and giving formal statements on universal in-context approximation of fully recurrent models including SSMs. |
Work
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2026.05 - Present Paris, France
Research Scientist Intern (Incoming)
Apple Machine Learning Research
Working with Sinead Williamson and Michael Kirchhof on uncertainty quantification for LLMs.
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2022.07 - 2023.01 Oxford, UK
Machine Learning Research Intern
DeepMind / Torr Vision Group, University of Oxford
Designed a framework for faithful knowledge distillation. Derived LP-based bounds on teacher–student confidence disagreement enabling formal analysis. Developed methods yielding more calibrated student models; resulted in our paper Faithful Knowledge Distillation.
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2019.07 - 2019.09 Durham, UK
Summer Research Student
University of Durham
Proved new identities relating polylogarithmic integrals to multiple zeta values with Prof. Herbert Gangl.
Education
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2023.10 - Present Oxford, UK
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2022.09 - 2023.08 Edinburgh, UK
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2016.10 - 2020.07 Durham, UK
Publications
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2025 -
2025 Towards Label-Free Biological Reasoning Synthetic Dataset Creation via Uncertainty Filtering
NeurIPS Workshop on Efficient Reasoning 2025
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2024 Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models
NeurIPS Datasets and Benchmarks 2024
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2024 -
2023 Faithful Knowledge Distillation
arXiv 2023
Awards
- 2023
MSc Artificial Intelligence Class Prize
University of Edinburgh
Awarded to the student who attained the highest overall mark in the MSc Artificial Intelligence course.
- 2020
Percy Heywood Prize
Department of Mathematical Sciences, University of Durham
Awarded to a student graduating with an MMath whose performance is outstanding in the final year.
- 2019
John Crowther Prize
University College, University of Durham
Awarded for performance in third-year Mathematics examinations.
Skills
| Programming Languages | |
| Python | |
| Bash | |
| Java | |
| SQL | |
| Matlab |
| Machine Learning | |
| PyTorch | |
| GPyTorch | |
| Transformers | |
| OpenAI | |
| WandB | |
| scikit-learn | |
| NumPy | |
| Pandas | |
| SciPy |
| Research Areas | |
| AI safety | |
| LLM generalisation | |
| statistical learning theory | |
| LLMs | |
| NLP | |
| uncertainty quantification | |
| calibration | |
| Bayesian methods | |
| variational inference |
| Other Tools | |
| Git | |
| GurobiPy | |
| NLTK | |
| Datasets |
Volunteer
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2023.09 - 2024.06 OXAi Education Team Member
University of Oxford
Created blog posts and teaching materials on machine learning, ranging from introductory concepts to advanced topics for undergraduates and researchers.
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2020.09 - Present Mathematics and AI Tutor
University of Oxford and Online
Teach MSc-level Reinforcement Learning, Statistical Learning Theory (OPUS program) and tutor GCSE/A-Level and undergraduate mathematics.
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2019.10 - 2020.06 Mathematics Teaching Assistant
University of Durham
Marked and provided detailed feedback on second-year Algebra coursework, ensuring clarity and rigor.