Meet our current students. 2024 Cohort Melina MüllerData-driven model-based control of neural dynamics to restore function in human neurological conditionsSupervisors: Nina Kudryashova, Matthias Hennig Artur Miralles MéharonMultimodal ML for stratifying people with Myalgic Encephalomyelitis using data from the Visible app and the DecodeME genetics projectSupervisors: Chris Ponting, Dr Sjoerd Beentjes Bianca BrancoPredicting Heterogeneity in Depression Across the Life-CourseSupervisors: Heather Whalley, Professor Peggy Seriès Zhijie YaoInferring cell state in disease progression from gene expression data using tractable deep probabilistic modelsSupervisors: Linus Schumacher, Guillaume Blin Jamie DaviesSelf-supervised Learning for Cardiac MRI: Fast Image Reconstruction and PrescriptionSupervisors: Mehrdad Yaghoobi, Lucy Kershaw Núria Fàbrega RibasMining the Multi-Omic LiteratureSupervisors: Ian Simpson, Kenny Baillie Rodrigo Lara MolinaRobust experimental design with an antibiotic resistance modelSupervisors: Michael Gutmann, Andrea Weisse Emilia AgasiNetwork-based multimodal AI approaches to address heterogeneity in ovarian cancerSupervisors: Ian Simpson, Charlie Gourley Rishi RamessurReliable Vision-Language Models for Healthcare ApplicationsSupervisors: Steven McDonagh, Professor Sotirios Tsaftaris Binjie ChenEngineering enzyme replacement therapies for Mucopolysaccharidosis Type IVASupervisors: Giovanni Stracquadanio, Eve Miller-Hodges Elisa CastagnariImproving digital healthcare solutions with data interoperability and large language modelsSupervisors: Ian Simpson, Ole Eigenbrod, Pinar Wennerberg 2025 Cohort Tesni WalshAI and the Dark Genome: Using protein-DNA structure modelling and genomic language models to predict the impacts of non-coding genetic variationSupervisors: Joseph Marsh, Simon Biddie Mario Navarro VeigaGenetic regulation of antibiotic resistance in the major pathogen Klebsiella pneumoniaeSupervisors: Andrea Weisse, Thamarai Dorai-Schneiders Anthos MakrisDiscover novel imaging features in OCTs and/or statistical data that predict visual outcome after macular hole surgery and that can be used to inform clinical decision makingSupervisors: Heather Yorston, Stuart King Eleanor HarrisonHow do different ways of making a home warmer affect risk of preschool respiratory infections? Using artificial intelligence to make homes and children healthier.Supervisors: Olivia Swann, Sohan Seth Mohammad KouliAI-driven continuous physiological monitoring to predict deterioration following surgerySupervisors: Ewen Harrison, Annemarie Docherty Joanne IgoliCausal healthcare analytics for Real-World Evidence with Targeted Learning: A cross-disciplinary, cross-sector approachSupervisors: Sjoerd Beentjes, Ava Khamseh Hailey DeckersStratifying cancer treatment responses in mesothelioma with AI-driven bioimagingSupervisors: Carsten Hansen, Yunjie Yang Nardiena PratamaExplainable and Transparent AI models for Glioma Diagnosis from Brain MRISupervisors: Ajitha Rajan, Paul Brennan Stephen BinaansimFinding the rhythm: detection of metabolic events in mental health conditions from time series dataSupervisors: Karl Burgess, Diego Oyarzun Iva JankovicAI for discovering affordable therapies against neglected tropical diseasesSupervisors: Diego Oyarzun, Shay Cohen Sim Mei ChooOperationalizable clinical risk predictions using machine learning-driven multi-state modelsSupervisors: Sohan Seth, Bruce Guthrie Nikou MoradiArtificial Intelligence EEG Biomarkers for Neurodevelopmental DisordersSupervisors: Alfredo Gonzalez-Sulser, Javier Escudero Han JiangAI-driven investigation of the neural circuit dynamics supporting online motor adaptationSupervisors: Ian Duguid, Angus Chadwick Lachin SoufizadehUsing machine-learning approaches to predictively genotype ASD model rats based upon large-scale, high-density neuronal network dataSupervisors: Peter Kind, Paul Rignanese This article was published on 2025-09-18
