Universal Testing Machine & BioPuls Biobath
| Manufacturer | Instron |
|---|---|
| Model | 68SC-1 |
Research
Funding & Partners
Our research is supported by competitive federal grants and strong cross-institutional collaborations.
01
Machine Learning
Research Lead Sanjian Zhang AI-driven simulation accelerators and predictive models that replace expensive finite element solvers with learned surrogate representations.
Data Analysis & Machine Learning
We design data pipelines and machine learning models to process experimental and clinical data, classify motility patterns, and accelerate prediction and decision support.
Our machine learning research also explores spatiotemporal modeling of cardiac dynamics. Sanjian Zhang studies how to integrate cardiac structures reconstructed from CT/MRI with physiological signals, such as blood pressure, and clinical variables to model and predict cardiac motion throughout the cardiac cycle.
HeartSimSage: Attention-Enhanced Graph Neural Networks
Our flagship ML framework converts cardiac finite element meshes into graph structures, learning the relationship between geometry, material properties, loading conditions, and tissue deformation, at 13,000× GPU acceleration and 190× CPU acceleration compared to traditional FEA, with median error under 0.13%.
GraphSAGE Topology
Flexible node connectivity on unstructured cardiac meshes.
Laplace-Dirichlet Encoding
Mesh-aware spatial embedding via Laplace equation solutions.
Attention Mechanism
Adaptive message passing with dynamic neighbor weighting.
Subset Training
Efficient subgraph sampling to reduce memory footprint.
Project Visualization
13,000×
GPU Acceleration
190×
CPU Acceleration
0.13%
Median Error
0.28mm
Max Displacement Error
Related Publications
- Shi L*, Chen Y, Vedula V. Journal of Computational Physics, 2026. HeartSimSage framework for AI-accelerated cardiac biomechanical simulations.
Interested in This Research?
Tell us your major, year, and what caught your eye. We'll reply within a week.
02
Multiscale & Multiphysics Simulation
Research Lead Nanlong Sun Cross-scale computational modeling and coupled multiphysics simulations, from molecular ion channels to whole-organ electromechanics.
Imaging, Reconstruction & Digital Twins
We integrate CT scans, endoscopy images, and manometry data from clinical collaborators to build accurate 3D models of the stomach, esophagus, and heart. These models are the geometric foundation for every digital twin we construct.
On top of that geometry, we develop patient-specific digital twins that couple tissue mechanics with electrical activity to simulate how each organ contracts, moves, and responds to disease or surgical intervention.
3D-0D Electromechanical Coupling
Implicit coupling framework that integrates 0D ion-based electrophysiology models with 3D finite-element solid mechanics, enabling patient-specific simulation of cardiac and gastric motility.
Figure 1: Multiscale modeling of a patient-specific cardiac digital twin.
3D Solid Mechanics
Nonlinear finite-element mechanics with large deformation kinematics.
0D Electrophysiology
Ion-channel models of electrical activity (e.g., Hodgkin-Huxley type).
Mechano-Electric Feedback
Bidirectional coupling between tissue deformation and electrical activity.
Implicit Coupling
0D and 3D models solved together within one implicit coupling framework.
4D Patient-Specific Imaging
Integration of time-phase CT and MRI imaging to construct personalized 3D organ geometries that evolve physiologically throughout the cardiac or respiratory cycle.
Segment Multi-atlas + deep-learning organ segmentation
Morph Non-rigid registration for motion estimation
Mesh Hex-dominant discretization with quality control
Project Visualization
Electromechanical Digital Twin Simulation video coming soon
Applications
01
Personalized Diagnosis
Patient-specific mechanical predictions for improved clinical accuracy.
02
Surgical Planning
Pre-operative biomechanical simulation of bariatric and GI procedures.
03
Gastric Pacemaker Design
Optimizing electrode placement for electrical stimulation devices.
04
Population-Scale Studies
Efficient computation enabling large-cohort biomechanical research.
Related Publications
- Shi L*, Chen IY, Vedula V. Computer Methods in Applied Mechanics and Engineering, 2026. Personalized multiscale modeling of left atrial mechanics and blood flow.
- Vedula V, Shi L, Gan BB. APS Division of Fluid Dynamics, 2024. Multiscale electromechanics modeling framework.
Interested in This Research?
Tell us your major, year, and what caught your eye. We'll reply within a week.
03
Constitutive Modeling
Research Lead Yue Li Physics-based material models that capture the complex, nonlinear behavior of biological soft tissues under large deformation.
Why Material Models Matter
Every simulation we run depends on how accurately it describes the tissue itself. Stomach, cardiac, and other soft tissues show both elastic recoil and time-dependent relaxation, so our models are calibrated against the mechanical tests performed in our lab.
Hyper-Viscoelastic Constitutive Framework
We develop microstructure-informed material models that combine hyperelastic equilibrium response with viscoelastic rate-dependent behavior, which is essential for accurate simulation of soft tissues that exhibit both elastic recoil and time-dependent relaxation.
Figure 1: Computational biomechanics modeling of soft tissue.
Microstructure-Informed
Material parameters tied to collagen fiber architecture and ground substance properties.
Large Deformation
Validated across physiological strain ranges (up to 40–60%) with anisotropic fiber reinforcement.
Viscoelastic Coupling
Prony-series based time-dependent response with separable hyperelastic equilibrium.
Cross-Validation
Identified via inverse calibration against biaxial, uniaxial, and shear experimental data.
Project Visualization
Soft Tissue Material Response Simulation video coming soon
Related Publications
- Shi L*, Myers K. Journal of the Mechanics and Physics of Solids, 2026. Microstructure-informed hyper-viscoelastic model for gastric tissue.
Interested in This Research?
Tell us your major, year, and what caught your eye. We'll reply within a week.
04
Experiments & Testing
Explore our laboratory equipment and contact us to discuss experimental testing and research collaborations.
Biomaterials Testing System
| Manufacturer | CellScale |
|---|---|
| Model | Contact us for model details |
Cryostat
| Manufacturer | Sakura |
|---|---|
| Model | Tissue-Tek Cryo3 Flex |
Interested in Collaborating?
Share your research goals, sample type, testing needs, and expected timeline with our team.