Dr Sandeep Shirgill PhD, MSci

Sandeep Shirgill

School of Mathematics
Research Fellow

Contact details

Email
s.shirgill@bham.ac.uk
View my research portal
Address
Watson Building
School of Mathematics
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Sandeep Shirgill is a postdoctoral research fellow specialising in mathematical biology. Her work focuses on applying an interdisciplinary approach, combining both mechanistic and data-driven models to predict cell behaviour under various conditions.

Qualifications

  •  Member of the Institute of Mathematics and its Applications (IMA)
  • PhD in Mathematical Biology, University of Birmingham, 2024
  • MSci in Theoretical Physics and Applied Mathematics, 2019

Biography

Sandeep Shirgill graduated from the University of Birmingham in 2019 with an MSci in Theoretical Physics and Applied Mathematics, specialising in mathematical biology for her Master's project. She went on to complete an interdisciplinary PhD at the University of Birmingham in 2024, investigating the effects of metal ions released from bioactive glass fibres on wound-associated biofilms, under the supervision of Dr Sarah A. Kuehne, Dr Gowsihan Poologasundarampillai and Dr Sara Jabbari.

She is currently a postdoctoral researcher at the University of Birmingham, where her research focuses on the mathematical modelling of antimicrobial resistance in bacteria. Her work combines mechanistic mathematical models with experimental data to investigate bacterial responses to antimicrobial treatment, with a particular emphasis on understanding antimicrobial accumulation, membrane permeability, intracellular binding and efflux, and how these processes influence treatment efficacy.

Previously, her research focused on applying machine learning and deep learning techniques to analyse the spatial organisation of proteins in cells imaged using single-molecule localisation microscopy, developing computational methods to identify and compare nanoscale protein organisation.

Teaching

LM Topics in Applied Mathematics (4TAM) (Lecturer)

Research

  •  Mathematical modelling of antimicrobial accumulation and antimicrobial resistance in bacteria
  • Mechanistic modelling of membrane permeability, intracellular binding and antimicrobial efflux
  • Utilising deep learning to compare protein organisation in cells imaged with single-molecule localisation microscopy
  • Predicting the diagnosis of acute compartment syndrome using machine learning methods
  • Developing novel antibacterial biomaterials for wound-healing applications
  • Mechanistic modelling of bacterial biofilm treatment and wound healing through partial differential equations
  • Parameter estimation and model inference for biological systems

Publications

Recent publications

Article

Shirgill, S, Begum, N, Kuehne, SA, Poologasundarampillai, G, Jabbari, S & Ward, J 2026, 'A partial differential equation model of a novel treatment for chronic wound biofilm infections', Clinical Biomechanics, vol. 132, 106744. https://doi.org/10.1016/j.clinbiomech.2025.106744

Savoye, K, Nieves, DJ, Shirgill, S, Lewis, A, Spill, F & Owen, DM 2025, 'Measuring the similarity of single-molecule localization microscopy derived marked point clouds', Biophysical Journal, vol. 124, no. 18, pp. 2931-2940. https://doi.org/10.1016/j.bpj.2025.07.035

Shirgill, S, Nieves, D, Pike, J, Ahmed, M, Abbott, H, Baragilly, M, Savoye, K, Worboys, JD, Hazime, KS, Bruggeman, E, Garcia, A, Williamson, DJ, Rubin-Delanchy, P, Peters, R, Davis, DM, Henriques, R, Lee, SF & Owen, D 2025, 'Nano-org, a functional resource for single-molecule localisation microscopy data', Nature Communications, vol. 16, 8674. https://doi.org/10.1038/s41467-025-63674-x

Other report

Ghumra, A (ed.), Taskin, A, Das, A, Abbas, A, Yang, C, Owen, D, Barbour, E, Allman, E, Al-Gburi, F, Khaleel, F, Wilson, G, Luo, G, Saddal, H, Hein-Paar, J, Riddell, J, Lewis, J, Nutter, K, Mijic, L, Butt, L, Tavakol , M, Shymanovich, M, Zhang, M, B M A J Aldoub, M, Soulas, O, Russell, P, Broderick, R, Shirgill, S & Wetz , S 2026, Birmingham Environment for Academic Research: Case Study Vol. 5. University of Birmingham. https://doi.org/10.25500/epapers.bham.00004428

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