BIOGRAPHY

Harry Hongxiang Lin, PhD, is a Research Associate in the Centre for Medical Image Computing, Department of Computer Science at University College London. He received a BSc degree and MSc in Mathematics respectively from Xiamen University (2011) and Fudan University (2014), China. He was awarded the PhD from Department of Mechanical Engineering, the University of Tokyo, Japan (2017). In 2017-2018, he was a Project Researcher affiliated to both Fluids Engineering Laboratory and Medical Equipment Engineering Laboratory at the University of Tokyo.

His research interests cover Image Quality Transfer using deep neural networks, biomedical image processing (Super-resolution, deblurring, etc.) and inverse problem theory on medical imaging (Magnetic Resonance Imaging/Ultrasound Computed Tomography/Photoacoustic Imaging).

He serves as a reviewer for the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Uncertainty for Safe Utilization of Machine Learning in Medical Imaging with MICCAI and Scientific Reports. He was awarded the first-place winner of ABCD Neurocognitive Prediction Challenge as a co-author. He was presented Teijin-Kumura scholarship sponsored by the Teijin Scholarship Foundation, Japan in 2015-2017. He was presented SEUT RA Fellowship offered by School of Engineering, the University of Tokyo in 2014-2017. He was presented Outstanding Graduate Student of Shanghai City in 2014.

EDUCATION / QUALIFICATIONS

• 2011: B.Sc. School of Mathematical Sciences, Xiamen University. (Numerical Mathematics)
• 2014: M.Sc. School of Mathematical Sciences, Fudan University. (Numerical Mathematics)
• 2017: Ph.D. Department of Mechanical Engineering, University of Tokyo. (Medical Imaging)

RESEARCH AND PROFESSIONAL EXPERIENCE

Hongxiang(Harry)’s current research interests cover Image Quality Transfer using deep neural networks, biomedical image processing (Super-resolution, deblurring, etc.) and inverse problem theory on medical imaging (Magnetic Resonance Imaging/Ultrasound Computed Tomography/Photoacoustic Imaging).

He is now a Research Associate in the Centre for Medical Image Computing, Department of Computer Science at University College London. He joins the project "Image Quality Transfer" for epilepsy diagnosis in sub-Saharan Africa. In 2017-2018, he was a Project Researcher affiliated to both Fluids Engineering Laboratory and Medical Equipment Engineering Laboratory at the University of Tokyo.

SELECTED PUBLICATIONS

1. Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator. Hongxiang Lin, Matteo Figini, Ryutaro Tanno, Stefano B Blumberg, Enrico Kaden, Godwin
2. Ogbole, Biobele J Brown, Felice D'Arco, David W Carmichael, Ikeoluwa Lagunju, Helen J Cross, Delmiro Fernandez-Reyes, Daniel C Alexander. In MICCAI-MLMIR, 2019.
3. Evaluation of Adjoint Methods in Photoacoustic Tomography with Under-Sampled Sensors. Hongxiang Lin, Takashi Azuma, Mehmet Burcin Unlu, Shu Takagi. In MICCAI, 2018.
4. Multi-frequency accelerating strategy for the contrast source inversion method of ultrasound waveform tomography using pulse data. Hongxiang Lin, Takashi Azuma, Xiaolei Qu, Shu Takagi. In SPIE Medical Imaging 2017: Ultrasonic Imaging and Tomography, 2017.
5. Robust contrast source inversion method with automatic choice rule of regularization parameters for ultrasound waveform tomography. Hongxiang Lin, Takashi Azuma, Xiaolei Qu, Shu Takagi. Japanese Journal of Applied Physics, 2016.

a href="https://scholar.google.com/citations?user=eRV0CGcAAAAJ&hl=en</a></h4>"