Dr Yingjing Feng PhD

Dr Yingjing Feng

Institute of Metabolism and Systems Research
Research Fellow

Contact details

Email
y.feng.3@bham.ac.uk
Twitter
@SeffyYjFeng
View my research portal
Address
Centre for Systems Modelling and Quantitative Biomedicine
Institute of Metabolism & Systems Research
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Yingjing Feng is a Research Fellow at the Centre for Systems Modelling and Quantitative Biomedicine (IMSR - UoB), with Professor John Terry. She has a strong interest in the interdisciplinary research of computing, mathematics and biomedical engineering. Her research is focused on developing statistical and mechanistic modelling methods to advance the diagnosis and treatment of human diseases.

Qualifications

  • PhD in Applied Mathematics and Scientific Computing, University of Bordeaux, 2021
  • MSc in Computing (Machine Learning), Distinction, Imperial College London, 2016
  • BSc in Computer Science, First-Class Honours, University of Birmingham, 2015
  • BEng in Software Engineering, Sun Yat-Sen University,  2015

Biography

During her MSc study at Imperial College London in 2015 to 2016, Yingjing developed a strong interest in applying machine learning to biomedical applications, while working on developing novel techniques to automate catheter ablation therapies using machine learning with Dr Su-Lin Lee, which was awarded a Distinguished MSc Project Prize.

In 2018, she began her PhD study in Applied Mathematics and Scientific Computing at the University of Bordeaux with Dr Edward Vigmond, under European Union’s Marie Skłodowska-Curie Horizon 2020 Innovative Training Network - Personalised In-silico Cardiology (PIC). During her PhD, she was awarded a Rosanna Degani Young Investigator Award at the Computing in Cardiology Conference (2019, Singapore). In 2021, she defended her PhD thesis entitled "Spatiotemporal machine learning on scanner-free body surface potential imaging aided by multiscale modeling for personalized atrial fibrillation treatment".

In March 2022, she joined the University of Birmingham to start working as a Research Fellow with Prof. John Terry at the Centre for Systems Modelling and Quantitative Biomedicine. She will investigate perturbation and treatment for epilepsy.

Research

Yingjing is interested in combining interpretable statistical modelling with mathematical modelling to improve treatment of epilepsy, cardiac arrhythmia and other pathologies. Her current research includes:

  • Spatiotemporal machine learning (including deep learning) on ECG and EGG recordings.
  • Pattern discovery and survival analysis of clinical treatment.
  • Data assimilation of mathematical models with patient data.
  • Validation of novel mapping and treatment methods.

Other activities

  • Public engagement
  • Supervision of master students

Publications

For a full list of publications, please see Dr Feng's Google scholar page.

Feng Y, Roney CH, Bayer JD, Niederer SA, Hocini M, Vigmond EJ. Detection of focal source and arrhythmogenic substrate from body surface potentials to guide atrial fibrillation ablation. PLoS Comput Biol. 2022 Mar 21;18(3):e1009893.

Langfield P, Feng Y, Bear LR, Duchateau J, Sebastian R, Abell E, Dubois R, Labrousse L, Rogier J, Hocini M, Haissaguerre M, Vigmond E. A novel method to correct repolarization time estimation from unipolar electrograms distorted by standard filtering. Med Image Anal. 2021 Aug;72:102075.

Corral-Acero J, Margara F, Marciniak M, Rodero C, Loncaric F, Feng Y, Gilbert A, Fernandes JF, Bukhari HA, Wajdan A, Martinez MV, Santos MS, Shamohammdi M, Luo H, Westphal P, Leeson P, DiAchille P, Gurev V, Mayr M, Geris L, Pathmanathan P, Morrison T, Cornelussen R, Prinzen F, Delhaas T, Doltra A, Sitges M, Vigmond EJ, Zacur E, Grau V, Rodriguez B, Remme EW, Niederer S, Mortier P, McLeod K, Potse M, Pueyo E, Bueno-Orovio A, Lamata P. The 'Digital Twin' to enable the vision of precision cardiology. Eur Heart J. 2020 Dec 21;41(48):4556-4564.

Feng Y, Guo Z, Dong Z, Zhou XY, Kwok KW, Ernst S, Lee SL. An efficient cardiac mapping strategy for radiofrequency catheter ablation with active learning. Int J Comput Assist Radiol Surg. 2017 Jul;12(7):1199-1207. doi: 10.1007/s11548-017-1587-4. Epub 2017 May 5.

View all publications in research portal