
Yidan Xue
@yidanxue
Postdoc at CIMIM @UoMPankhurst | previously @MathsCU @OxUniMaths @oxengsci @SchoolOfEng_UoE | biomedical fluid dynamics & in-silico trials ๐ง ๐ซ๐ฉธ๐๐ฉป
ID: 783342014674771969
https://yidanxue.github.io 04-10-2016 16:24:25
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๐ AI's role in high-stakes decisions is growing, but uncertainty lurks beneath! ๐ Our new paper explores personalised uncertainty quantification (PUQ) challenges in AI applications like healthcare & finance. Dive into the future of AI fairness here: nature.com/articles/s4225โฆ ๐



In microfluidic networks, flow oscillations and chaos can emerge even without external modulation or deformable structures. Adilson E. Motter and colleagues show that fluid inertia drives the responsible mechanism, expanding on-chip flow control design. ๐ go.aps.org/4iQkeYx



Stephen Payne (NTU Taiwan) conducted multi-scale modelling of the effects of ageing, #hypertension and exercise on the #cerebral vasculature in this recent #Research article ๐ด๐ง ๐ Read it here: buff.ly/rufHvJ1


Super excited, our latest paper is out in IEEE TMI! ๐ A new deep learning model for 3D anatomical shape generation, advancing in-silico trials. ๐ Read more: ieeexplore.ieee.org/document/10988โฆ Stay tuned โ the final version will be out soon! Prof Alejandro Frangi FREng CISTIB #InSilicoTrials #digitaltwin










Happy to share my new paper in Proc R Soc A Royal Society Publishing 'Computing Stokes flows in periodic channels via rational approximation'. Check it out if you are interested in rational approximation, Stokes flows, or chaotic advection: royalsocietypublishing.org/doi/full/10.10โฆ


๐ Is simplicity always better? ๐ค Ockhamโs Razor โ๏ธ says yes, but modern science often thrives in complexity ๐. This episode dives into the tug-of-war between parsimony and intricate models. Can science strike a balance? โ๏ธ ๐๏ธ Tune in to rethink what makes discovery


We have a Research Associate position Prof Alejandro Frangi FREng and British Heart Foundation, on applying advanced machine learning techniques to automate and accelerate the analysis of large-scale cardiac imaging datasets. Details are below: jobs.ac.uk/job/DNG726/resโฆ Apply by Tuesday 10 June 2025!