Projects Led by Dr Allan Tucker


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

  • 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

  • Autonomous Navigation of Quadrocopter Using An External Camera

Led by Dr Veronica Vinciotti

  • Novel Regression Models for Dynamic and Discrete Response Data Under L1 and Differentiable Penalties
  • Novel multilevel models in healthcare
  • Multilevel latent-class models in healthcare

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