Keynote Speakers


  • Prof. Yu-Dong Zhang
    University of Leicester, UK
    IET Fellow

    Prof. Yu-Dong Zhang received his PhD degree from Southeast University in 2010. He worked as a postdoc from 2010 to 2012 in Columbia University, USA, and as an assistant research scientist from 2012 to 2013 at Research Foundation of Mental Hygiene (RFMH), USA. He served as a full professor from 2013 to 2017 in Nanjing Normal University, where he was the director and founder of Advanced Medical Image Processing Group in NJNU. Now he serves as Professor in Department of Informatics, University of Leicester, UK.
    He was included in “Most Cited Chinese researchers (Computer Science)” by Elsevier from 2014 to 2018. He was the 2019 recipient of “Highly Cited Researcher” by Web of Science. He won “Emerald Citation of Excellence 2017” and “MDPI Top 10 Most Cited Papers 2015”. He was included in "Top Scientist" in Guide2Research. He published over 160 papers, including 16 “ESI Highly Cited Papers”, and 2 “ESI Hot Papers”. His citation reached 10096 in Google Scholar, and 5362 in Web of Science.
    He is the fellow of IET (FIET), and the senior members of IEEE and ACM. He is the editor of Scientific Reports, IEEE Transactions on Circuits and Systems for Video Technology, etc. He served as the (leading) guest editor of Information Fusion, Neural Networks, IEEE Transactions on Intelligent Transportation Systems, etc. He has conducted many successful industrial projects and academic grants from NSFC, NIH, Royal Society, and British Council.
    Speech Title: Medical Image Analysis via Deep Learning
    Personal Link

  • Prof. Manuchehr Soleimani
    University of Bath, UK

    Professor Soleimani leads the Engineering Tomography Lab (ETL) group he found in 2011. ETL works in partnership with leading UK and international research teams and many industrial partners.
    Particular interests are in ultrasound tomography, electrical and electromagnetic imaging and X-ray CT, nonlinear inverse problems, machine learning, and multi-modality imaging.
    The main areas are in, "Machine Learning", "AI", “Super-Sensing”, "X-ray CT", "Ultrasound tomography", “Multi-modality Tomography”, “Inverse Problems”, and “Electrical and Electromagnetic Tomography”, "Bio-impedance imaging", including: 1) Medical imaging , 2) Industrial process tomography, 3) Tomography for material characterisation.
    Professor Soleimani has led the University of Bath's collaborations with CERN through CMS research and educational partnership established from 2019. This followed a highly successful medical imaging project between Bath and CERN leading to a joint open source software platform TIGRE.
    Speech Title: Multi modality tomographic imaging for structural and functional imaging
    Personal Link

  • Dr. Richard Jiang
    Lancaster University, UK

    Dr. Richard Jiang is a Senior Lecturer (Associate Professor) in the School of Computing & Communications at Lancaster University, UK. He currently holds a prestigious Leverhulme Trust Research Fellowship. He is a Fellow of HEA, an Associate Member of EPSRC College, and an EPSRC RISE Connector.
    Dr Jiang's research interest mainly resides in the fields of Biometrics, Privacy & Security, Intelligent Systems, and Biomedical Image Analysis. His recent research has been supported by grants from EPSRC (EP/P009727/1), Leverhulme Trust (RF-2019-492), Qatar National Research Fund (NPRP No.8–140-2–065) and other industry/international funders. He has supervised and co-supervised over 10 PhD students. He authored over 60 publications and is the lead editor of three Springer books. He served as a TPC member and a reviewer for various international conferences and journals.
    Personal Link

  • Dr. Edwin Abdurakman
    City, University of London, UK

    Dr Edwin Abdurakman is the programme director for Diagnostic Radiography undergraduate studies in the School of Health Sciences at City, University of London. He acquired his PhD from the Nottingham Trent University in the medical applications of Magnetic Resonance Imaging (MRI). His novel research focused on developing and testing microbubble-based contrast agents to measure pressure variations in the human stomach with MRI, a collaborative work between the Nottingham Trent University and the world distinguished MRI research centre, the Sir Peter Mansfield Imaging Centre at the University of Nottingham. The research aimed to use microbubbles as a pressure probe for MRI gastrointestinal applications, which will be useful as a diagnostic tool in diagnosing patients with functional dyspepsia conditions. His latest article has been published in the highly rated peer-reviewed journal Magnetic Resonance in Medicine.
    Dr Abdurakman holds a Fellowship of the Higher Education Academy. He is an appointed member of the British Institute of Radiology (BIR) MR special interest group, and an active member of the Society and College of Radiographers (SCoR) as well as the European Society of Magnetic Resonance in Medicine and Biology (ESMRMB).
    Speech Title: Measuring pressure in the stomach using MRI and microbubble-based contrast agents