MixingLab
Biophysical and technological fluid mixing at the University of Rochester
116 & 112 Hopeman Engineering Building
ABOVE:
OPENINGS: We're seeking a postdoctoral researcher to build a foundation model of brain-wide fluid circulation using artificial intelligence.
PUBLISHED: Our paper MR-AIV reveals in vivo brain-wide fluid flow with physics-informed AI has been published in Sci. Adv. and featured by U of R. Our paper Quantifying cerebrospinal fluid flow in pial perivascular spaces of rats has been published in Fluids Barr. CNS. Our paper A time-dependent, brain-wide model of solute transport in the glymphatic system has been published in J. R. Soc. Interface.
PUBLISHED: Our paper MR-AIV reveals in vivo brain-wide fluid flow with physics-informed AI has been published in Sci. Adv. and featured by U of R. Our paper Quantifying cerebrospinal fluid flow in pial perivascular spaces of rats has been published in Fluids Barr. CNS. Our paper A time-dependent, brain-wide model of solute transport in the glymphatic system has been published in J. R. Soc. Interface.
Fluid mixing is both beautiful and devilishly difficult to understand, predict, or control. We study how fluid flows and the materials they carry change over space and time, primarily with application to cerebrospinal fluid flow in the brain and to liquid metals technologies.
