Yuan Shen

Independent Research Fellow

Computing and Technology


Yuan Shen is a Independent Research Fellow in the School of Science & Technology.

Career overview

Yuan Shen obtained his diploma and PhD degree in Physics at University of Zurich, Switzerland. After his PhD study, he moved on to receive research training in the area of Computational Statistics and Machine Learning at University of Warwick, Aston University, and University of Birmingham. In 2017, He took up a lecturer position at Department of Mathematical Science of Xi'an Jiaotong - Liverpool University (XJTLU). In 2018, he left XJTLU for an Independent Research Fellow position at NTU.

Research areas

  1. Machine Learning for Signal Processing (MLSP)
    1. Computational methods for Bayesian inference in dynamical systems;
    2. Machine learning in the space of dynamical system models;
    3. Gaussian process based surrogate model for Bayesian inverse problem;
    4. Probabilistic modelling
      1. Probabilistic modelling of time series data (e.g. fractal time series)
      2. Probabilistic modelling of imaging data (e.g. multispectral retinal images)
      3. Probabilistic modelling of spatiotemporal data (e.g. functional MRI)
  2. MLSP for Medical Informatics
    1. State-of-the-arts learning paradigms for medical informatics. Examples:
      1. Learning Using Privileged Information (LUPI) for Cost-effective Diagnosis of Mildly Cognitive Impairment
      2. Learning in Model Space for Medication Response Prediction of Attention Deficit Hyperactivity Disorder
      3. Hierarchical  mixture-of-experts modelling for Management of epilepsy patients
    2. Big data techniques for medical applications
      1. Big Data Techniques: (1) deep neural network; (2) higher-order tensor factorisation
      2. Medical Informatics Applications: (1) Cancer Genomics; (2) Sleep and Epilepsy

Research projects

  1. Markov Chain Monte Carlo for Models in Stochastic Geometry (an EPSRC project led by Dr Thonnes at The University of Warwick);
  2. Variational Inference in Stochastic Dynamic Models (an EPSRC project led by Dr Cornford at Aston University);
  3. Multispectral Retinal Image Analysis: A new technique for the assessment of Age-related Macular Degeneration (a Dunhill Medical Trust project led by Dr Styles at The University of Birmingham)
  4. Unified probabilistic modelling of adaptive spatial temporal structure in the human brain (a BBSRC project led by Prof Tino at The University of Birmingham);
  5. Personalised medicine through learning in the model space (an EPSRC project led by Prof Tino at The University of Birmingham).

Student supervision

  1. PhD student projects
    • Nahed Alowadi (completed in 2018) – Population-level spatio-temporal probabilistic modeling of fMRI data (Co-supervision with 25% capacity, Director of study is Prof Peter Tino at School of Computer Science of The University of Birmingham)
    • Hanin Alahmadi (completed in 2018) – Efficient Feature Extraction Methods for High-order Tensor Data (Co-supervision with 25% capacity, Director of study is Prof Peter Tino at School of Computer Science of The University of Birmingham);
  2. MSc/MRes student projects
    • Gulrukh Turabee (completed in 2019) – Sleep stage classification with all-night  EEG recordings: a deep learning approach (Co-supervision with 50% capacity at Nottingham Trent University)
    • Ruchi Bharat Patel (completed in 2020) – Unsupervised feature selection for gene scoring: a deep learning approach (Nottingham Trent Univeristy);
  3. FYP student projects
    • Shengjie Sun (completed in 2018) – Efficient Markov Chain Monte Carlo Algorithms for Bayesian Inference in Dynamical Systems (Supervision at XJTLU)