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Research students


Research projects I offer are mainly in the research areas of Biomedical Engineering and Energy, and aim to various levels of ability. Hovewer, all undergraduate projects might potentially lead to a journal publication or a paper for a conference. If students wish to carry out a challenging and novel research they are welcome to speak with me. Most enthusiastic students who wish to continue their studies at a PhD level are very welcome to discuss their future plans and research interests, and I will be happy to advise them on the funding opportunities available at Warwick and better ways to transform their undegraduate research into future studies.


Undergraduate students

2013-14

  • Josh Williams 'MEASURING AND MODELLING THE INTERACTION BETWEEN HEART RATE AND RESPIRATION FOR VARIOUS PATTERNS OF RESPIRATION'
  • Sean Perry 'INVESTIGATION OF PHASE SYNCHRONISATION BETWEEN HEART AND RESPIRATION DYNAMICS FOR VARIOUS FREQUENCIES OF RESPIRATION'
  • Alexandru Coca 'STOCHASTIC MODELLING OF THE BEHAVIOUR OF A KITE IN A WIND TUNNEL'

2012-13

  • Torgyn Shaikhina (2012-13) 'NEURAL NETWORK MODELLING OF TRABECULAR BONE FOR HARD TISSUE ENGINEERING' This research project led to (i) International Vice Chancellor scholaship being granted to Torgyn to continue her research at PhD level at Warwick, (ii) a journal publication (article); (iii) an oral presentation 'Application of Machine Learning to hard tissue engineering' at the British Conference of Undergraduate Research - BCUR 2013

This study investigated the correlation of age in male and female specimens with physico-mechanical properties of trabecular bone including compressive strength, bone volume fraction, structural model index, trabecular thickness factor, level of inter-connectivity and pore morphology. An artificial neural network was designed to analyse 35 available samples in order to account for complex inter- dependencies of the key parameters in multi-dimensional space. Trained by using Levenberg-Marquardt back propagation algorithm, the network achieved regression factor of 0ยท96 by optimisation and showed that age correlates strongly with the physical properties of the bone affected by severe osteoarthritis. In addition, the compressive strength was found to be the most important factor for predicting
the bone aging. Within the limitations of the input data set, the model developed provides a reliable predictive tool to tissue engineering applications.

  • Yonah Park (2012-13) 'INVESTIGATION OF THE ROLE OF ANTIBODIES IN AN ANTIBODY INCOMPATIBLE RENAL TRANSPLANTATION'. This 3rd year project was carried out in line with EPSRC research project 'Novel approach to clinical data analysis: application to kidney transplantation' (PI: Dr Khovanova)

2011-12

  • Johannes Windelen (2011-12) 'ENERGY EFFICIENT SWITCHING IN NANOELECTROMECHANICAL MEMORY ELEMENTS' (article [2] published)

Pontryagin minimal energy control approach has been applied to minimise the switching energy in a nanoelectromechanical memory system and to characterise the global stability of the oscillatory states of the bistable memory element. A comparison of two previously experimentally determined pulse-type control signals with Pontryagin control function has been performed and the superiority of the Pontryagin approach with regard to the power consumption has been demonstrated. An analysis of the global stability has shown as to how the values of minimal energy can be utilized in order to specify equally stable states.

Postgraduate students (PhD)


Yan Zhang

Yan Zhang (2012-15) 'INFERENCE OF STOCHASTIC NONLINEAR EQUATIONS FOR CHARACTERISATION OF TRANSIENT RESPONSE IN BIOMEDICAL SYSTEMS'

This research project is concerned with studying of the role of antibodies in incompatible kidney transplantation (IKT). IKT allows transplanting patients across antibody barriers; but the techniques remain limited in their application due to the persistent high rate of acute rejection of transplanted kidneys. The role of the student in this research is the development and application of novel methodology beyond standard approaches of medical statistics to study how much and what antibody types can be tolerated by the immune system of kidney recipient in order to ensure safe acceptance of the donor kidney.

Torgyn Shaikhina


Torgyn Shaikhina (2013-17) 'ARTIFICIAL NEURAL NETWORKS FOR BIOMEDICAL DATA ANALYSIS IN DIABETES RISK PREDICTION AND HARD TISSUE ENGINEERING DECISION SUPPORT'

The project aims to develop Artificial Neural Network (ANN) to construct the best model configuration for determining tissue engineering strategies. The goal is to predict the trends in the mechanical properties as well as osteoblastic cell behaviour commonly encountered for patients with orthopaedic diseases. This will be achieved by applying ANN and other appropriate Machine Learning algorithms to the relevant datasets for specific orthopaedic conditions. The research will enable prediction of mechanobiological properties of hard tissue and advise both clinicians and tissue engineering practitioners to better manage skeletal replacement, analyse and correlate parametric variables and validate clinical outcomes.