School of Engineering
Computing and Technology Building, CM028
+44 (0) 1772 89 2890
Yu’s main research interests are: optimization methods and embedded system.
Yu is now leading the development of the MSc Applied Data Science course.
Yu completed his PhD study in 2010. This project was to develop a Mark II portable handheld device to assist dermatologists to in melanoma diagnosis. This project features a computer aided diagnosis system whose user experience is pretty much like using a digital camera, while giving fast and reliable clinical decision support. It was award a prize from the Skin Forum.
After his PhD, Yu worked on a crystallization monitoring project which involves observing very fine 3D particles in real time. This project was funded by TSB and it requires collaborations with pharmaceutical/instrumental companies such as Pfizer and Avantium. Yu formulated and tested different mechanical plots for this device, designed the data collection/visualization software.
Yu also worked on image processing algorithms for digital histopathology applications in the WELMEC project in Leeds. Yu developed algorithms to mark the cells in microscope images, evaluating the amount of stains within one digital slide etc.
Song, Zhuoyi, Zhou, Yu and Juusola, Mikko (2017) Modeling elucidates how refractory period can provide profound nonlinear gain control to graded potential neurons. Physiological reports, 5
Song, ZY, Zhou, Y and Juusola, M (2016) Random Photon Absorption Model Elucidates How Early Gain Control in Fly Photoreceptors Arises from Quantal Sampling. Frontiers in Computational Neuroscience, 10 .
Pretorius, AJ, Zhou, Yu and Ruddle, R (2015) Visual parameter optimisation for biomedical image processing. BMC Bioinformatics, 16 (S9). pp. 1-13.
Optimization and modelling, embedded systems.
Course leader of MSc Applied Data Science