Jinao Zhang
Also known as: Jake Zhang
Monash University
Research areas: Engineering · Biomedical Engineering · Elasticity and Material Modeling · Soft Robotics and Applications · Surgical Simulation and Training
About
Jinao Zhang, PhD
Jinao (Jake) Zhang is a Medical AI/ML Engineer specializing in AI-driven innovations for medical imaging. He designs AI/ML solutions to optimize diagnostic workflows and advance precision healthcare.
Prior to his current role, he held positions as a Postdoctoral Research Fellow and Senior Research Officer in the Biomechatronics, Robotics, and Automated Systems (BmRAS) Lab at Monash University, Australia. There, he contributed to interdisciplinary projects integrating AI, biomechanics, and robotics to develop next-generation medical technologies. He earned his PhD from RMIT University for his work on "Real-time Simulation of Soft Tissue Deformation for Surgical Simulation". He also holds a First-Class Honours Bachelor of Engineering in Mechanical Engineering from the same university.
His research spans Medical AI, Biomechanics, and Medical Image Analysis, with applications in diagnostic automation, minimally invasive surgery, and patient-specific modelling.
Open-source Contributions: https://github.com/jinaojakezhang.
Employment
-
Monash University Research Fellow2018 - 2021
-
Monash University Senior Research Officer2018 - 2018
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (23)
- Numerical modelling and experimental study of a super-coiled polymer for dual actuator-sensor applications Save
- A direct Jacobian total Lagrangian explicit dynamics finite element algorithm for real‐time simulation of hyperelastic materials Save
- Thermal Dose Modeling for Thermal Ablative Cancer Treatments by Cellular Neural Networks Save
- Towards real-time finite-strain anisotropic thermo-visco-elastodynamic analysis of soft tissues for thermal ablative therapy Save
- Fast computation of soft tissue thermal response under deformation based on fast explicit dynamics finite element algorithm for surgical simulation Save
- Fast computation of desired thermal dose: Application to focused ultrasound-induced lesion planning Save
- Neural network methodology for real-time modelling of bio-heat transfer during thermo-therapeutic applications Save
- Modeling of soft tissue thermal damage based on GPU acceleration Save
- Neural network modelling of soft tissue deformation for surgical simulation Save
- Fast explicit dynamics finite element algorithm for transient heat transfer Save
- Real-time computation of bio-heat transfer in the fast explicit dynamics finite element algorithm (FED-FEM) framework Save
- Heat conduction-based methodology for nonlinear soft tissue deformation Save
- Neural dynamics-based Poisson propagation for deformable modelling Save
- Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics Save
- GPU-ACCELERATED FINITE ELEMENT MODELING OF BIO-HEAT CONDUCTION FOR SIMULATION OF THERMAL ABLATION Save
- Ellipsoid bounding region-based ChainMail algorithm for soft tissue deformation in surgical simulation Save
- Deformable Models for Surgical Simulation: A Survey Save
- TEMPERATURE-DEPENDENT THERMOMECHANICAL MODELING OF SOFT TISSUE DEFORMATION Save
- Energy balance method for modelling of soft tissue deformation Save
- Energy propagation modeling of nonlinear soft tissue deformation for surgical simulation Save