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Dr Natasha Khovanova

NK

Dr Natasha Khovanova

Reader in Systems and Biomedical Engineering

Deputy Director of Graduate Studies in the School of Engineering

N dot Khovanova at warwick dot ac dot uk
+44 (0) 24 7652 8242

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Biography

Natasha Khovanova studied for her doctorate in the Department of Physics at Saratov State University (Russia) and has a PhD degree in Physical and Mathematical Sciences. After her graduation and before moving to the UK, she held an academic post in the same department.

She joined the School of Engineering of the University of Warwick in 2010 and is a Reader in the Systems and Information Engineering stream and EPSRC Fellow. She is also an Honorary academic at the University Hospital Coventry and Warwickshire. Before taking her appointment at the School of Engineering, she was based in the Department of Physics at Lancaster University

Research Interests

  • Identification, stability and control of linear and nonlinear systems with application to diabetes
  • Time series analysis of complex signals and synchronisation phenomenon with application to cardio-respiratory coupling
    • We study the underlying mechanisms governing the communication between the cardiovascular and respiratory systems with particular attention to the differences in athletes and non-athletes.
    • Our main attention is the novel experimental design and application of the concept of instantaneous phase to detect cardio-respiratory entrainment at various respiratory rates and to utilise this non-invasive measure for tracking a person’s athletic development.
  • Development of machine learning and artificial intelligence methods with applications to limited data in clinical settings
    • Our emphasis on the utility of machine learning for data-efficient classification, regression and survival analysis to overcome the common limitations inherent in routinely collected patient data, such as class imbalance, incomplete samples and limited data size, i.e.less than 10 observations per predictor variable.
  • Supervised and unsupervised machine learning and data-driven dynamic modelling with application to high-risk renal transplantation

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Teaching Interests

Current undergraduate courses
  • ES3C8 System Modelling and Control 
  • ES327 Individual research projects

Selected Publications

Latest Projects and Grants

  • Early diagnosis and prevention of complications of gestational diabetes via modelling the complex dynamics of blood glucose variations. Funded by UHCW NHS Trust and Dexcom, Jan 2021 - Jan 2026
  • Neutrophil Extracellular Traps as biomarkers of endothelial dysfunction and immunothrombosis in severe COVID-19 infection. Funded by Medical and Life Sciences Research Fund, Aug 2021- Jun 2022.
  • Understanding barriers to accurate early laboratory diagnosis and patient-centric control of gestational diabetes mellitus. Funded by EPSRC, Discipline Hopping Fellowship, 7 Jan 2021 - 1 Jun 2022
  • Gestational diabetes: early diagnosis and prevention of complications via modelling the complex dynamics of blood glucose variations. PhD Fellowship. Funded by UHCW NHS Trust, Jan 2019 - Jan 2022
  • Modelling of pathogenicity of donor-specific antibodies in kidney transplantation. Funded by UHCW NHS Trust, Oct 2017 - Apr 2021
  • Personalised predictive nonlinear systems modelling and control of blood glucose dynamics. Funded by UHCW NHS Trust, Jun 2016 - May 2019
  • A novel approach to clinical data analysis - application to kidney transplantation. Funded by EPSRC, Apr 2013 - Sept 2015
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