Hyogu Jeong

Queensland University of Technology

Australia

Research Interests

Explore related searches

Professors in Australia Professors in Fluid Mechanics Fluid Mechanics professors in Australia

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

Articles (9)

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Collaborators (9)

Batuwatta Gamage Chanaka Prabuddha

Queensland University of Technology

AUSTRALIA

View details

Zhongzheng Wang

Queensland University of Technology

AUSTRALIA

View details

Charith Rathnayaka

Lecturer

University of the Sunshine Coast

AUSTRALIA

View details

Yi Min Xie

Distinguished Professor and Director of Centre for Innovative Structures and Materials

RMIT University

AUSTRALIA

View details

Yixiang Gan

AUSTRALIA

View details

Azharul Karim

Queensland University of Technology

AUSTRALIA

View details

Yuantong Gu

Queensland University of Technology

AUSTRALIA

View details

Jean-Michel Pereira

Full Professor

École des Ponts ParisTech

FRANCE

View details

Emilie Sauret

Professor at Queensland University of Technology

Queensland University of Technology

AUSTRALIA

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Hyogu Jeong

Research Interests

Explore related searches

Contact this professor

Articles (9)

Fourier feature embedded physics-informed neural network-based topology optimization (FF-PINNTO) framework for geometrically nonlinear structures

A meshless Runge-Kutta-based Physics-Informed Neural Network framework for structural vibration analysis

A physics-informed neural network framework for multi-physics coupling microfluidic problems

A physics-informed neural network framework to investigate nonlinear and heterogenous shrinkage of drying plant cells

A complete Physics-Informed Neural Network-based framework for structural topology optimization

A novel physics-informed neural networks approach (PINN-MT) to solve mass transfer in plant cells during drying

Pore-scale modeling of multiphase flow in porous media using a conditional generative adversarial network (cGAN)

A physics-informed neural network-based surrogate framework to predict moisture concentration and shrinkage of a plant cell during drying

A general Neural Particle Method for hydrodynamics modeling

Collaborators (9)

Batuwatta Gamage Chanaka Prabuddha

Zhongzheng Wang

Charith Rathnayaka

Yi Min Xie

Yixiang Gan

Azharul Karim

Yuantong Gu

Jean-Michel Pereira

Emilie Sauret

Make your next move.