Students

Current PhD Students (Principal Supervisor)

  • Mark Chevallier (Applications of Formalised Mathematics and Logic to Reinforcement and Deep Learning, submitted, February 2023).
  • Jorge Gaete Villegas (Explainable AI for healthcare).
  • Filip Smola (Formal Modelling of Complex Systems via Compositional Approaches in Isabelle/HOL)
  • James Vaughan (Network Analysis for Mathematical Reasoning in Isabelle)
  • Jiawei Zheng (Probabilistic reasoning over processes)
  • Lauren DeLong (Neurosymbolic AI in medicine/healthcare)
  • Zonglin Ji (AI  for healthcare processes)
  • Richard Schmoetten (Formalisation of axiomatic Quantum Field Theory in Isabelle/HOL)
  • Fiona Smith (AI and medicine/healthcare)

Recent Masters Students

  • Scott O’Donoghue (2022, Applying Machine Learning and Interpretable Techniques to Persistent Critical Illness). Distinction level MSc thesis.
  • Callum Abbott (2021,  To Drain or Not to Drain? A Causal Investigation into the Efficacy of Subdural Drains in Preventing CSDH Recurrence), Winner of the MSc in Data Science prize in the School of Mathematics.
  • Mathis Gerdes (2021, A Mechanized Investigation of an Axiomatic System for Minkowski Spacetime), one of the outstanding MSc thesis of the academic year 2020-21.
  • Richard Schmoetten (2020, Mechanizing Minkowski spacetime). One of the outstanding MSc theses of the academic year 2019-20 and Winner of the MSc in Informatics thesis prize.
  • Colleen Charlton (2020, Interpretable Classifiers for Brain Tumour Prediction). In collaboration with the Centre for Clinical Brain Sciences, University of Edinburgh. One of the outstanding MSc theses of the academic year 2019-20.
  • Anita Klementiev (2020, Process Mining Techniques for Modelling Healthcare Patient Paths). Distinction level MSc thesis.
  • Simon Thorogood (2019, Machine learning prediction of graft and patient survival following liver transplantation). In collaboration with Oxford NHS Trusts and NHSBT. One of the outstanding MSc theses of the academic year 2018-19 and Winner of the MSc in Data Science thesis prize.
  • Callum Biggs O’May (2019, Machine learning based survival analysis for brain tumours). In collaboration with the Centre for Clinical Brain Sciences, University of Edinburgh.Edinburgh. One of the outstanding MSc theses of academic year 2018-19.
  • Jessika Rockel (2019, Formalization of proofs from Euler’s Differential Calculus in Isabelle).  One of the outstanding MSc theses of academic year 2018-19.
  • Ka Wing Pang (2019, Coinductive reasoning over streams in Isabelle/HOL). Distinction level MSc thesis.

Recent Interns

Past PhD Students (Principal Supervisor)

  • Imogen Morris (Formalization of Euler’s Introductio in Isabelle/HOL, 2022).
  • Jake Palmer (Formal Verification of Voting Algorithms in Isabelle, 2022).
  • Yaqing Jiang (Machine Learning for Inductive Theorem Proving, 2018).
  • Phil Scott  (Ordered Geometry in Hilbert’s Grundlagen der Geometrie, 2014)
  • Petros Papapanagiotou (A Formal Verification Approach to Process Modelling and Composition, 2014)
  • Laura Meikle (Intuition in Formal Proof: A Novel Framework for Combining Mathematical Tools, 2013)
  • Sean Wilson (Supporting Dependently Typed Functional Programming with Proof Automation and Testing, 2010)
  • Lucas Dixon (A Proof Planning Framework for Isabelle, 2006)
  • Ewen Maclean (Using Proof-Planning to Investigate the Structure of Proof in Non-Standard Analysis, 2003)

Past PhD Students (Second Supervisor, incomplete list)

  • Tom Ridge (2005)
  • Mark Collins (2005)
  • Zhiheng Huang (2005)
  • Jeremy Gow (2004)

Past MSc Students (Very incomplete list)

  • Victor Dumitrescu (MSc by research, 2016)
  • Phil Scott (2008)
  • Petros Papapanagiotou (2007)
  • Jonas Halvorsen (2007)
  • Chris Laumann (2004)
  • Robbert Brak (2004)
  • …

Past Undergraduate Students

  • Too many to mention (but if one of you is reading this: you were all special) 🙂

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