Staff
Tatiana Bubba

Department of Mathematical Sciences

Dr Tatiana Bubba

Research interests:

  • Inverse problems (in particular, tomography)
  • Sparse regularisation and optimisation (in particular, wavelet and shearlets)
  • Machine learning and deep learning in imaging

Tatiana’s work focusses on computational inverse problems, in particular tomographic imaging. These problems are generally ill-posed, even more so when the data available are scarce or limited. In this case, strategies from sparse regularisation and variational optimisation, especially based on multi resolution system such as wavelets and shearlets, have been very successful in the last 15 years, providing competitive solutions to these very challenging problems. Tatiana’s research revolves around combining such variational regularisation (or model-based) techniques with data-driven approaches, coming from machine and deep learning fields, in order to develop new paradigms of data-driven inversion.

 

LINKS:

Tatiana Bubba on the University of Bath Research Portal

Lead Supervisors

Eric Hester

  • Asymptotic analysis of PDEs
  • Spectral algorithms for numerical PDE solvers
  • Multiphase fluid mechanics
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Stephen Wilson

Department of Mathematical Sciences

  • Fluid mechanics, especially thin-film flows, rivulets and evaporating droplets.
  • Non-Newtonian fluid mechanics, especially liquid crystals and thixotropic fluids.
  • More generally, the use of a range of mathematical (namely asymptotic, analytical and numerical) methods to bring new insights into a wide range of “real world” problems.
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Michael Murray

Department of Mathematical Sciences

  • Optimization: implicit regularization, geometry of the loss landscape
  • Generalization: benign and tempered overfitting, phase transitions in performance with respect to compute and data
  • Understanding emerging paradigms in ML, e.g., in-context learning, transformers etc.
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Federico Cornalba

Department of Mathematical Sciences

  • Modelling of large-scale interacting particle systems
  • Analysis and numerics of stochastic PDEs of Fluctuating Hydrodynamics
  • Reinforcement Learning methods
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Avi Mayorcas

Department of Mathematical Sciences

  • Regularisation by noise in stochastic partial and ordinary differential equations
  • Stochastic quantisation of physical field theories
  • Game theory and mean field dynamics in macroeconomics and finance
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Christoforos Panagiotis

Department of Mathematical Sciences

  • Percolation and lattice spin models
  • Probability on groups
  • Self-avoiding walk
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Matthew Schrecker

Department of Mathematical Sciences

  • Analysis of Partial Differential Equations
  • Fluid dynamics (especially free boundary problems and nonlinear singularity formation)
  • Shock waves (their formation, structure and dynamics)
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Haiyan Zheng

Department of Mathematical Sciences

  • Adaptive designs in clinical trials
  • Bayesian data augmentation
  • Finite mixture distributions
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Andreas Kyprianou

Andreas was instrumental in the development of SAMBa and was Co-Director from its inception until the end of 2022. He has left the University of Bath to take up the role of Chair of Probability at the University of Warwick.

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Jennifer Tweedy

Department of Mathematical Sciences

  • Mathematical medicine
  • Fluid mechanics
  • Mathematical modelling
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