Low-Order Modeling and Machine Learning in Fluid Dynamics: General III

Presentations

• Early detection of global instability via a large language model

  ORAL

  Nov. 25, 2025, 12:50 PM – Nov. 25, 2025, 1:03 PM

  Presenters

  • Jun HUR

    • The Hong Kong University of Science and Technology

  Authors

  • Jun HUR

    • The Hong Kong University of Science and Technology

  • Jungjin Park

    • The Hong Kong University of Science and Technology

  • Zhijian YANG

    • The Hong Kong University of Science and Technology

  • Bo YIN

    • The Hong Kong University of Science and Technology

  • Larry K.B. Li

    • The Hong Kong University of Science and Technology

  View abstract →

• Developing a data-driven model for unsteady prediction of the flow features using the attention-based approach

  ORAL

  Nov. 25, 2025, 1:03 PM – Nov. 25, 2025, 1:16 PM

  Presenters

  • Hamid Reza Karbasian

    • Southern Methodist University

  Authors

  • Hamid Reza Karbasian

    • Southern Methodist University

  • yassine hafiane

    • SMU

  View abstract →

• Scale Aware Deep Learning for Precipitation Prediction with Hybrid Loss Swin Transformer U-Net

  ORAL

  Nov. 25, 2025, 1:16 PM – Nov. 25, 2025, 1:29 PM

  Presenters

  • Jun Park

    • KAIST

  Authors

  • Jun Park

    • KAIST

  • Changhoon Lee

    • Yonsei University

  View abstract →

• Modeling convective heat transfer in a cavity flow using physics-informed neural networks

  ORAL

  Nov. 25, 2025, 1:29 PM – Nov. 25, 2025, 1:42 PM

  Presenters

  • YI-TING HE

    • National Tsing Hua University

  Authors

  • YI-TING HE

    • National Tsing Hua University

  • Ching Chang

    • National Tsing Hua University

  View abstract →

• A Hybrid Reduced-Order Modeling Framework for Accelerating Physics-Informed Neural Networks in Modeling Flow Instabilities

  ORAL

  Nov. 25, 2025, 1:42 PM – Nov. 25, 2025, 1:55 PM

  Publication: No paper has been published yet. The manuscript for this work is in progress, and we plan to publish it in Physics of Fluids.

  Presenters

  • Sangeetha S

    • Indian Institute of Technology Madras

  Authors

  • Sangeetha S

    • Indian Institute of Technology Madras

  • Vallabh Deogaonkar

    • Indian Institute of Technology Madras

  • Arjun Jagannathan

    • Indian Institute of Technology, Madras

  • Abhilash Somayajula

    • Indian Institute of Technology Madras

  View abstract →

• Pipe flow reconstruction using a novel physics-informed machine-learning technique

  ORAL

  Nov. 25, 2025, 1:55 PM – Nov. 25, 2025, 2:08 PM

  Presenters

  • Evan Yeremy

    • University of Alberta

  Authors

  • Evan Yeremy

    • University of Alberta

  • Suyash Verma

    • Univ of Alberta

  • Arman Hemmati

    • Univ of Alberta

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• Coarse-to-fine variational inference with physics-informed deep learning for complex fluid motion estimation

  ORAL

  Nov. 25, 2025, 2:08 PM – Nov. 25, 2025, 2:21 PM

  Presenters

  • Li Wei

    • Shanghai Jiao Tong University

  Authors

  • Li Wei

    • Shanghai Jiao Tong University

  • Xiaoxian Guo

    • Shanghai Jiao Tong University

  View abstract →

• Local Constraint Neural Operator for Discretization-Invariant Super-Resolution Turbulent Flow Prediction

  ORAL

  Nov. 25, 2025, 2:21 PM – Nov. 25, 2025, 2:34 PM

  Presenters

  • Jungwon Heo

    • Yonsei University

  Authors

  • Jungwon Heo

    • Yonsei University

  • Changhoon Lee

    • Yonsei University

  View abstract →

• Towards Optimal Sensor Trajectory for Flow Reconstruction

  ORAL

  Nov. 25, 2025, 2:34 PM – Nov. 25, 2025, 2:47 PM

  Presenters

  • Anand Karki

    • University of Waterloo

  Authors

  • Anand Karki

    • University of Waterloo

  • Oleksandr Reshetar

    • University of Waterloo, Department of Engineering

  • Roberto Guglielmi

    • University of Waterloo, Applied Mathematics

  • Zhao Pan

    • University of Waterloo, Mechanical & Mechatronics Engineering

  View abstract →