“Surgery is anatomy.
Anatomy is geometry.
Geometry is the heart of mechanics.”
— the lab’s working axiom
We work at the boundary between physical science and surgical medicine. The lab studies how shape—at every scale from a lipid film to the aortic wall—controls how tissues fail, how implants seal, and how surfaces remain clean. We translate this into tools that read the geometry of a single patient and predict what their disease will do next.
Read on
Luka Pocivavsek, MD PhD
Associate Professor of Surgery · Vascular Surgeon · Physicist
Luka Pocivavsek trained as a physicist and a surgeon at the same institution in which the lab now sits. His doctoral work—published in Science and Soft Matter—established a quantitative theory for how thin elastic membranes wrinkle and fold under compression. The translational consequence of that theory is the line of thought our lab still follows: shape is a diagnostic. The curvature of an aortic arch, the seal of an endograft, the topography of a vascular surface—each carries a mechanical signature that predates the clinical event by years.
Clinically, Dr. Pocivavsek is an open and endovascular vascular surgeon at the University of Chicago Medicine. His practice spans complex aortic reconstruction, cerebrovascular disease, and peripheral vascular surgery. He is a member of the Committee on Medical Physics and the Pritzker School of Molecular Engineering.
Six interlocking threads, all variations on a single theme: how does geometry encode mechanical risk in a living tissue?
Thin elastic films on liquid substrates do not buckle uniformly—they localize their stress into folds. Our 2008 Science paper established a generic wavelength selection law for this transition, and the work has since become a reference point for soft-matter mechanics of lipid monolayers, polymer sheets, and biological membranes.
Working with longitudinal CT cohorts we develop curvature- and torsion-based descriptors that map how aortic dissections evolve and how abdominal aortic aneurysms grow. Recent work uses sparse identification of nonlinear dynamics (Z‑SINDy) to extract patient-specific growth laws from imaging.
A stent graft is a deformable cylinder mounted inside a curved, pulsatile vessel. We characterize the geometric and material conditions under which a proximal seal will hold versus migrate, with a long-term goal of patient-specific landing-zone selection prior to EVAR/TEVAR.
Surfaces that wrinkle dynamically can shed adherent fouling. Published in Nature Physics and Biomaterials, this thread uses active wrinkling as a strategy for keeping vascular and prosthetic surfaces clean without chemical coatings.
Computational fluid dynamics of arteriovenous fistulae and complex congenital pathways. We study how wall shear distribution drives neointimal hyperplasia and how surgical geometry can be reshaped to extend patency.
We build open-source tooling for principal-curvature, second-fundamental-form, and torsion estimation on noisy 3D surfaces from clinical CT. Our codebases (anato-shape and anato-poly-smooth-curve) are used by the lab and by external collaborators.
A complete and current list lives on Google Scholar. The work below shaped how the lab thinks today.
We release tooling on the lab's GitHub organization. Pull requests welcome.
Curvature calculations on 3D surface meshes of complex anatomies. Notebooks and helper functions for principal curvatures, mean and Gaussian curvature, normal estimation.
Polynomial smoothing and curvature estimation of noisy biological surfaces, with application to aortic morphology. Companion code for the methods paper.
Analysis code for "Dynamic Temporal Modeling of Abdominal Aortic Aneurysm Morphology with Z-SINDy." Sparse identification of nonlinear growth dynamics from CT.
Research data & analysis for the 2024 PLOS Computational Biology publication on aortic dissection geometry and surgical outcome prediction.
Curvature, torsion, geodesics on patient-specific meshes.
Hyperelastic vessel-wall models and endograft contact mechanics.
Pulsatile flow in arch, fistula, and congenital geometries.
Resolved structure from tissue to monolayer.
Compression isotherms and fold nucleation in lipid films.
Graph neural networks for growth mapping; sparse system identification.
Inquiries about postdoctoral, graduate, and undergraduate positions are welcome.