Dr Shufan Yang

Dr Shufan Yang


I am an Associate Professor in Computational Intelligence & Optimisation at the Institute of Medical & Biological Engineering, School of Mechanical Engineering, University of Leeds. I was also appointed as an Honorary Associate Professor in Medical Technologies at the Research Department of Orthopaedics and Musculoskeletal Science, University College London. I obtained my PhD degree in Computer Science from the University of Manchester, UK, in 2010 under the supervision of Professor Steve Furber. I was a Royal Academy of Engineering Industrial Fellow from 2022 to 2023 with Codeplay Software Ltd (acquired by Intel Software Inc), Co-I for a Dstl-funded project 'Exploring Decision-Making Processes in Autonomous Systems' in 2015, and PI for two Innovate UK funded Knowledge Transfer Partnerships projects.

My research has been funded by EU Horizon, Dstl, Innovate UK, EPSRC, the Royal Society of Edinburgh, and the Royal Academy of Engineering. In the past, I have worked on deep reinforcement learning, system-on-chip, and computational neuroscience research areas, publishing over 50 scientific articles in top-tier journals and conferences, including Nature, IEEE Transactions on Medical Imaging, Parallel Computing, etc. I have served on many research award panels for Innovate UK, EPSRC peer review, Royal Academy of Engineering Research Fellow peer review, Canada Foundation for Innovation, and the Dutch Research Council. I have also been involved in multiple STEM public engagement activities with Nuffield Health and currently serves as a council member of the BCS, the Chartered IT Council.

Research interests

My research focuses on using deep neural network algorithms for optimisation in engineering problems, particularly in translational therapeutics for neurodiverse diseases, the analysis of medical and biomedical images for biomarker extraction, and data-driven healthcare utilizing edge machine learning acceleration technologies. My research interests include complexity science, biological informatics, deep reinforcement learning, and advanced sensor instruments. I specialize in hardware-software acceleration for artificial neural network imaging reconstruction in ultrasound imaging, photoacoustic computed tomography, optical coherence tomography, and radar-based human activity recognition using micro-Doppler techniques for resource-limited platforms.

I advocate for open science, particularly in developing digital tissue phantoms. One of my ongoing projects can be found on my GitHub page, accessible at WOLVS/standardised-image-reconstruction: The IPASC standardised image reconstruction project.

I am also passionate about open hardware and have participated in competitions for the last decade. My past winning projects include:

<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://eps.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>


  • PhD in Computer Science

Professional memberships

  • Charted Engineer (CEng)
  • Senior IEEE
  • MBCS
  • FHEA

Student education

  • Robotics and Machine Intelligence
  • Professional Project

Current postgraduate researchers

<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>