Xiaoshui Huang is a postdoctoral research associate with the Image-X Institute at The University of Sydney and a researcher with the Medical Physics Group at the Ingham Institute. He completed his PhD in computer science from the University of Technology Sydney. In this role, he brings his experience in machine learning and algorithm development to analyse the protocol compliance with the lung patient outcome to improve patient care. His current research found that lung cancer patients’ treatments are below 20% in compliance with Australia eviQ protocol. Another aspect of his research is to use deep learning to personalise image guidance to maximise radiotherapy treatment success. His main research interests lie in causal discovery, deep learning-based fiducial marker detection and 3D image processing. He has published 15 full papers and one abstract in ESTRO 2021. He serves as a reviewer for many computer science top conferences and top journals, for example, CVPR2021, ICCV2021, NeuIPS2021, ICLR2022, IJCAI2021, TIP, IJCV and TMM.
What would you say is your most valuable personal attribute that has helped you succeed?
My most valuable personal attribute that has helped me succeed is perseverance.
Do you think it is important to have a mentor?
It is very important to have an experienced and successful mentor since the mentor can teach us a lot of valuable things other than work itself.
What have you learnt during your career to increase your resilience?
During my postdoctoral career, I have learnt to be kind to others and be strict to ourselves.
What is your ideal holiday?
My ideal holiday is to close the phone and do whatever follows the heart.
What are your favourite past-times or hobbies?
In my spare time, I enjoy jogging, watching movies and playing computer games.
