 | Jacques Fleuriot | My main field of research lies in AI Modelling, which spans areas such as interactive theorem proving, formal verification, process modelling, and machine learning and Explainable AI techniques applied to healthcare and other complex domains. |
 | Paola Galdi | Machine learning and statistical modelling for biomedical data, multimodal data integration, network-based modelling. |
 | Ricardo Contreras | Monitoring of dynamic process compositions and data processing with focus on older adults. |
 | Guillermo Romero Moreno | Interdisciplinary research in AI, ML, and network science applied to various areas, such as politics, health, biology, robotics, etc. |
 | Jake Palmer | Formalising and verifying voting methods using interactive theorem proving in Isabelle/HOL. |
 | Mark Chevallier | Formal verification of machine learning algorithms and their properties. |
 | Nuša Farič | Nuša has interests in psychology, health psychology, AI, femtech, women’s health, health content on Wikipedia and innovative health solutions. She studied at the University of Glasgow (BSc Hons Psychology), UCL (MSc Health Psychology), and PhD (Health Psychology and Informatics for the UCL Institute of Health Informatics). |
 | Jorge Gaete Villegas | Explainable AI for healthcare. |
 | James Vaughan | Applications of ML and Network Theory in Automated Theorem Proving; Business Process Modelling and IoT. |
 | Filip Smola | Interactive theorem proving and formal verification, with application to automatic differentiation, category theory and process calculi. |
 | Jiawei Zheng | Uncertainty in complex event processing, process mining, and conformance checking. |
 | Ramon Fernández Mir | Interactive theorem proving and convex optimisation applied to hybrid systems verification. |
 | Lauren DeLong | Artificial Intelligence and medicine/healthcare. |
 | Zonglin Ji | Artificial Intelligence for ICU care and predictions |
 | Richard Schmoetten | Formalising Haag-Kastler Nets in Higher-order Logic. |
 | Konstantin Georgiev | My current interests lie in applied Data Science for geriatric medicine, particularly rehabilitation needs and trajectories of older patients. This includes conducting observational studies on the impact and constraints of treatments performed on patients with frail and multimorbid conditions. |
 | Matt Whelan | My main interests are in AI applications in psychiatry, with a particular focus on predicting mental/cognitive health outcomes from sleep and activity patterns. |
AIML Associates/Interns
 | Alex Hyman | Interested in exploring the world of Isabelle and formally verifying mathematics |
 | Petros Papapanagiotou | AI for collaborative workflow management. This includes formal verification, process modelling, analysis and optimisation, IoT, event-based and distributed systems, and social machines. |
Recent AIML Alumni
Simon U (BSc, 2023) | Enhancing deep learning model performance by imposing temporal feature for fine-grained human activity recognition |
Gareth Dawson (BSc, 2023) | A front-end graphical user interface for the Proter Simulator |
Matt Whyte (MSc, 2023) | Generating efficient PyTorch code from formal specification (Outstanding Informatics MSc in Artificial Intelligence thesis 2023) |
Mark Chevallier (PhD, 2023) | Applications of Formalised Mathematics and Logic to Reinforcement and Deep Learning |
Imogen Morris (PhD, 2022) | Mechanising Euler’s use of Infinitesimals in the Proof of the Basel Problem |
Scott O’Donoghue (MSc, 2022) | Applying Machine Learning and Interpretable Techniques to Persistent Critical Illness |
Carlin Mackenzie (MInf, 2022) | Developing an online proof archive for formalized mathematics |
Dawson Silkenat (BSc, 2022) | Formalisation of Lagrangian Mechanics in Isabelle/HOL |
Lars Werne (BSc, 2022) | Formalisation of Newtonian Physics in Isabelle/HOL |
Martin Lewis (BSc, 2022) | Web development for business process simulation |
Michal Sadowski (BSc, 2022) | Workflow execution and management |
Dimitris Christodoulou (MInf, 2022) | Activity tracking and localisation using Wi-Fi data |
Michal Baczun (MInf, 2022) | Business process simulation |
Petros Papapanagiotou (Chancellor’s Fellow, 2022) | AI for collaborative workflow management. This includes formal verification, process modelling, analysis and optimisation, IoT, event-based and distributed systems, and social machines. |
Callum Abbot (MSc, 2021) | To Drain or Not to Drain? A Causal Investigation into the Efficacy of Subdural Drains in Preventing CSDH Recurrence (MSc in Data Science thesis prize) |
Yefei Chen (MSc, 2021) | Designing checklists generated from process models |
Qi Chen (MSc, 2021) | Delay visualization in process timelines |
Mathis Gerdes (MSc, 2021) | Investigating causality in axiomatic Minkowski spacetime using Isabelle/HOL |
Cyan Hou (MSc, 2021) | A web framework for negotiation strategies in multi-agent meeting scheduling |
Shilin Li (MSc, 2021) | Incorporating cultural preferences in meeting scheduling applications |
Alice Johansen (BSc, 2021) | Formalisation of proofs from Euler’s Foundations of Differential Calculus using Nonstandard Analysis (I) |
Richard Stansfield (BSc, 2021) | Formalisation of proofs from Euler’s Foundations of Differential Calculus using Nonstandard Analysis (II) |
Richard Schmoetten (MSc, 2020) | Axiomatic Minkowski Spacetime in Isabelle/HOL (MSc in Informatics thesis prize) |
Colleen Charlton (MSc, 2020) | Interpretable classifiers for brain tumour prediction (Outstanding Informatics MSc thesis 2020) |
Anita Klementiev (MSc, 2020) | Process mining techniques for modelling healthcare patients’ paths in the ICU/CCU |
Yannan Huang (MSc, 2020) | Process analytics for the training of future doctors |
Demetris Louca (MSc, 2020) | Analysis of process miners |
Yaqing Jiang (PhD, 2019) | Machine Learning for Inductive Theorem Proving |
Callum Biggs-O’May (MSc, 2019) | Investigating Brain Cancer Survival with Machine Learning (Outstanding Informatics MSc thesis 2019) |
Kezhi (Bill) Chen (MSc, 2019) | Delay Analysis in Manufacturing Process |
Ka Wing Pang (MSc, 2019) | Exploring Streams with Isabelle/HOL |
Jessika Rockel (MSc, 2019) | Exploring Euler’s Foundations of Differential Calculus in Isabelle/HOL using Nonstandard Analysis: Logarithms (Outstanding Informatics MSc thesis 2019) |
Simon Thorogood (MSc, 2019) | Predicting Transplant and Patient Survival Following Liver Transplantation using Machine Learning (MSc in Data Science thesis prize 2019) |
Zuzana Frankovska (BSc in Computer Science and Mathematics, 2019) | Exploring Euler’s Foundations of Differential Calculus in Isabelle/HOL using Nonstandard Analysis: Geometric Series and Arcsine |
Filip Smola (Summer Intern, 2019) | DigiFlow: Digitizing Industrial Workflow, Monitoring and Optimization |
Kyriakos Katsamaktsis (MMath, 2018; Summer Intern, 2019) | Exploring Euler’s Notions of Orders of Infinity in Isabelle/HOL using nonstandard analysis (MMaths Project Prize 2018) |
Nigel Hussain (MSc, 2018) | Business Process Modelling of Care Pathways for HIV Patients |
James Vaughan (MSc, 2018) | Learning over Isabelle’s Dependency Graphs |
Hristo Saev (BSc, 2018) | Developing a Social, Open, Peer Review Web Platform |
Ruitao Yi (Summer Intern, 2018) | Formalization of the Backpropagation Algorithm |
Steven Obua (Senior Research Fellow, 2014-2017) | ProofPeer: Collaborative Theorem Proving |
Phil Scott (Research Fellow, 2014-2017) | ProofPeer: Collaborative Theorem Proving |
Imogen Morris (BSc, 2017) | An Axiomatic Formalisation of Trigonometric Functions in Isabelle (BSc Maths Project Prize 2017) |
Jake Palmer (MSc, 2017) | A Mechanized Investigation of an Axiomatic System for Minkowski Spacetime |
Eirini Papakosta (MSc, 2017) | An Interactive, Web-based Platform for Pulmonary Rehabilitation |
Lie (Jessie) Ma (MSc, 2017) | An Interactive, Web-based Platform for Pulmonary Rehabilitation |
Daniel Raggi (Research Assistant, 2017) | Entailment Graphs in Isabelle/HOL |
Alisa Dewanti (MSc, 2016) | Developing workflow-based guidelines for burns care in Scotland |
Vanessa Hanschke (MSc, 2016) | A Social Machine for the Heart Manual Programme |
Sebastian Schulze (BSc, 2016; Summer Intern 2016) | Evolving Neural Networks for Natural Deduction Proofs |