• Ph. D. University of Chicago 1999
  • M. Sc. University of Chicago 1993
  • B. A. Haverford College, Haverford, PA 1992 Magna Cum Laude, high departmental honors
  • Exchange Oxford University, Oxford, UK 1991
  • Phi Beta Kappa 1991


  • 2006-present: Lecturer & Senior Lecturer in Mathematics, Loughborough University.
  • 2005-2006: Associate Professor of Mathematics, Lawrence University.
  • 1999-2005: Assistant Professor of Mathematics, Lawrence University.

Professional Memberships:

Research leadership

  • Director of Plastrax research group for the development of technologies for tracking and characterising microplastics

Research interests in statistics and data science:

  • Analysis of high dimensional and functional data
  • Metabolomics, including statistics for biomarker identification and process control
  • Statistical methods for image data, particularly in physical and materials sciences
  • Topological and geometric methods in statistics and machine learning
  • Analysis of clinical data for epidemiology and medical policy making
  • Signal processing for nanopore sensors

Research interests in mathematics:

  • Elliptic PDE on noncompact and singular manifolds
  • Pseudodifferential operator calculi
  • Hodge and signature theorems for singular and noncompact manifolds
  • Intersection cohomology and its generalizations
  • Monopole and other moduli spaces arising in physics
  • Numerical techniques for spectral problems with singular potentials
  • Applications of category theory to systems engineering

Research videos and slides

Introductory talks

Research talks

External research activities

Lecturer at graduate summer schools:

External workshops/semesters organised:

  • “Hausdorff Institute for Mathematics workshop in honour of Prof. Werner Mueller’s 60th birthday” HIM, 2010;
  • “Topology of Stratified Spaces” MSRI, 2008;
  • MSRI semester, “Analysis on Singular Spaces” 2008;
  • “L^2-harmonic forms in geometry and string theory” ARCC, 2004

Taught Modules 2021/22

  • MAP501 Statistics for Data Science (part of the MSc in Data Science)

Data Analysis MOOC

  • Data Tells a Story: Introduction to data science for social science and humanities

Current PhD Students

  • Lei Ye: Computational Statistics for Brain and Muscle Diffusion Tensor Image Analysis (joint with D. Zhou and B. Li)
  • Steff Farley: Characterising the Geometry of Image Space of Nanostructures for Inferential Analysis of Dewetting Processes and Computational Models (joint with A. Soltoggio)
  • Kerry Rosenthal: Statistical Methods for Compact Mass Spectrometry in Metabolomics (joint with M. Lindley, M. Turner, and E. Ratcliffe)
  • Nayani Adhikari: Diagnosis and Retraining of Asthmatic and Dysfunctional Breathing Techniques Using Opto-Electronic Plethsymography (joint with S. Winter and M. Pain)
  • Jennifer Ferris: Statistical Models of Lower Limb Soft Tissue for Integration into Multimodal Imaging Technologies (joint with S. Winter and D. Zhou)

Plastrax Research Group PhD Students

  • Imoleayomide Ajayi: Data Science for Microplastics Characterisation (joint with Z. Zhou and M. Platt)
  • Symiah Barnett: At-site Microplastic Monitoring for Rivers and Marine Environments (Funded by CENTA, joint with M. Platt and E. Baynes)
  • Shadab Soheilian: Characterisation of Micro- and Nano-plastics in Complex Systems (joint with Z. Zhou)
  • Elizabeth Christie: Developing New Analytical Technology for the Rapid Identification and Quantification of Micro/Nanoplastics (joint with M. Platt and E. Baynes)
  • Beth Jordan: Engineered Polymetric Micro- and Nanoplastics (Supervisors F. Hatton, B. Cousins, E. Baynes)

Past PhD Students

  • Yanis Bahroun (Loughborough University, 2020)
  • Navid Bari (Loughborough University, 2017)
  • Vladimir Lukiyanov (Loughborough University, 2016)
  • Kamil Mroz (Loughborough University, 2014)
  • Louis Omenyi (Loughborough University, 2014)
  • Nikolaos Roidos (Loughborough University, 2010)

Students interested in undertaking a self-funded PhD with me are encouraged to get in contact!

Possible project areas include:

  • Inverse problems for nanopore sensors
  • Category Theory for architecture definition in systems engineering and digital twins
  • Bayesian methods for data integration in materials science
  • Shape statistics in biomechanics
  • Mixed methods (AI/statistics/social sciences/humanities) for understanding mechanisms of inequality in science.