Projects Led by Dr Allan Tucker



Led by Dr Stephen Swift

  • An investigation into the application of CNN’s to classify Leukemia subtypes from blood stain images
  • The use of Consensus techniques to predict the number of groups within data clustering
  • Mining GitHub project meta-data to improve the software modularisation problem
  • An improved Iterated Local Search for discrete combinatorial optimization
  • Sentiment analysis ensembles to predict the trajectory of online hate forums

Led by Professor Xiaohui Liu

  • EC Horizon 2020, INTEGRADDE: “Intelligent data-driven pipeline for the manufacturing of certified metal parts through direct energy deposition processes”, CI
  • EC Horizon 2020, Z-BRE4K: “Real-Time Adaptable Machine Simulation models wrapped around Physical Systems for accurate predictive maintenance, towards zero-unexpected-breakdowns and increased operating life of Factories”, CI
  • EC 7th Framework, EWATUS: “An Integrated Support System for Efficient Water Usage and Resources Management”, CI
  • GSK/EPSRC CASE Award, “Predicting chromatin status from differential expression profiles”, PI

Led by Profesor Zidong Wang

  • Liu / Wang: EC Horizon 2020 [2020-2024], DIG_IT: “A Human centred Internet of Things Platform for the Sustainable Digital Mine of the Future”
  • Liu / Wang: EC Horizon 2020 [2018-2022], INTEGRADDE: “Intelligent Data-Driven Pipeline for the Manufacturing of Certified Metal Parts through Direct Energy Deposition Processes”
  • Liu / Wang: EC Horizon 2020 [2017-2021], Z-BRE4K: “Real-Time Adaptable Machine Simulation Models Wrapped around Physical Systems for Accurate Predictive Maintenance, towards Zero-unexpected-Breakdowns and Increased Operating Life of Factories”
  • Deep learning techniques with applications to healthcare data (Royal Society, Royal Academy of Engineering, European Union)
  • Advanced algorithm development for big data analysis in social networks (Royal Society, European Union)
  • Big data learning-based QoS analysis and estimation of cloud-services (Royal Society, National Science Foundation of China)
  • Dynamic state estimation for power grids with unconventional measurements (Royal Society, Royal Academy of Engineering, European Union)
  • Mathematical challenges in complex networks (Royal Society, China Scholarship Council)


Led by Dr Annette Payne

  • What Works for Well Being (ESRC)
  • Identifying risk factors associated with student failure and poor performance using learning analytics

Led by Dr Stainslao Lauria

  • INTEGRADDE (EU Horizon2020 2019-2023)
  • DIG_IT (EU Horizon2020 2020-2023)

Led by Dr Isabel Sassoon

Led by Dr Alaa Marshan

Led by Nadine Aburumman

  • Learning to Care: the Early Development of Empathy in Brain and Behaviour (VR CAVE and Eye Tracking device) with the ToddlerLab, Birkbeck, University of London.
  • Exploring the Effect of Vibration Feedback in VR Training Settings with my PhD student Rania Xanthidou.

Led by Dr Yongmin Li

  • Retinal image analysis
  • Personalised re-marketing
  • AI-assisted tax assessment

Led by Dr Lianghao Han

  • Software Environment for Actionable & VVUQ-evaluated Exascale Applications (SEAVEA)

Led by Dr Keming Yu

  • Weibull regression for dispersion and lifetime data
  • Predicting coating defect size on pipelines
  • Bayesian discrete quantile regression
  • Online remote condition monitoring using statistical analysis
  • Novel extreme regression analysis for material failure and corrosion
  • Quantile regression for modelling the remaining life of buried pipelines