Chin Chun Ooi

Orcid: 0000-0003-4813-4529

According to our database¹, Chin Chun Ooi authored at least 40 papers between 2021 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

Meta-Inverse Physics-Informed Neural Networks for High-Dimensional Ordinary Differential Equations.

[BibT_eX]

[DOI]

Zhao Wei

Kenneth Hor Cheng Koh

CoRR, May, 2026

Transferable Physics-Informed Representations via Closed-Form Head Adaptation.

[BibT_eX]

[DOI]

CoRR, April, 2026

FFV-PINN: A Fast Physics-Informed Neural Network with Simplified Finite Volume Discretization and Residual Correction.

[BibT_eX]

[DOI]

CoRR, March, 2026

Bridging Computational Fluid Dynamics Algorithm and Physics-Informed Learning: SIMPLE-PINN for Incompressible Navier-Stokes Equations.

[BibT_eX]

[DOI]

CoRR, March, 2026

Scale-PINN: Learning Efficient Physics-Informed Neural Networks Through Sequential Correction.

[BibT_eX]

[DOI]

CoRR, February, 2026

PINEAPPLE: Physics-Informed Neuro-Evolution Algorithm for Prognostic Parameter Inference in Lithium-Ion Battery Electrodes.

[BibT_eX]

[DOI]

CoRR, February, 2026

Evolutionary Optimization of Physics-Informed Neural Networks: Evo-PINN Frontiers and Opportunities.

[BibT_eX]

[DOI]

IEEE Comput. Intell. Mag., February, 2026

Out-of-Distribution Generalization for Neural Physics Solvers.

[BibT_eX]

[DOI]

CoRR, January, 2026

Physics-Informed Uncertainty Enables Reliable AI-driven Design.

[BibT_eX]

[DOI]

CoRR, January, 2026

Scenario-based daily risk assessment for indoor airborne transmission with coupled agent-based and computational fluid dynamics models.

[BibT_eX]

[DOI]

J. Comput. Sci., 2026

2025

CompARE: A Computational framework for Airborne Respiratory disease Evaluation integrating flow physics and human behavior.

[BibT_eX]

[DOI]

CoRR, November, 2025

Differentiable Physics-Neural Models enable Learning of Non-Markovian Closures for Accelerated Coarse-Grained Physics Simulations.

[BibT_eX]

[DOI]

CoRR, November, 2025

Parametric Expensive Multi-Objective Optimization via Generative Solution Modeling.

[BibT_eX]

[DOI]

CoRR, November, 2025

ExTrEMO: Transfer Evolutionary Multiobjective Optimization With Proof of Faster Convergence.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., February, 2025

Physics-Informed Neuro-Evolution (PINE): A Survey and Prospects.

[BibT_eX]

[DOI]

CoRR, January, 2025

A continuous encoding-based representation for efficient multi-fidelity multi-objective neural architecture search.

[BibT_eX]

[DOI]

Zhao Wei

Chin Chun Ooi

Yew-Soon Ong

Appl. Soft Comput., 2025

Evolvable Conditional Diffusion.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Estimating Airborne Transmission Risk for Indoor Space: Coupling Agent-Based Model and Computational Fluid Dynamics.

[BibT_eX]

[DOI]

Proceedings of the Computational Science - ICCS 2025, 2025

2024

Learning in Sinusoidal Spaces With Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Artif. Intell., March, 2024

Tailoring Generative Adversarial Networks for Smooth Airfoil Design.

[BibT_eX]

[DOI]

CoRR, 2024

Importance of Nyquist-Shannon Sampling in Training of Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2024

Towards End-to-End Prompt-Vision-Physics Neural Network for Fast Design Discovery.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Artificial Intelligence, 2024

Soft Constraint in Local Structure Approximation-PINN.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Artificial Intelligence, 2024

2023

Generalizable Neural Physics Solvers by Baldwinian Evolution.

[BibT_eX]

[DOI]

Joshua Shao Zheng Low

My Ha Dao

Yew-Soon Ong

CoRR, 2023

LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2023

Neuroevolution of Physics-Informed Neural Nets: Benchmark Problems and Comparative Results.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022

JAX-Accelerated Neuroevolution of Physics-informed Neural Networks: Benchmarks and Experimental Results.

[BibT_eX]

[DOI]

Nicholas Wei Yong Sung

CoRR, 2022

Robustness of Physics-Informed Neural Networks to Noise in Sensor Data.

[BibT_eX]

[DOI]

CoRR, 2022

Physics Compliance as a Metric for Neural Network Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Graph Neural Network Based Surrogate Model of Physics Simulations for Geometry Design.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Design of Turing Systems with Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Tightening Regret Bounds for Scalable Transfer Optimization with Gaussian Process Surrogates.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

FastFlow: AI for Fast Urban Wind Velocity Prediction.

[BibT_eX]

[DOI]

Shi Jer Low

Venugopalan S. G. Raghavan

Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

Day-Ahead Forecasting for the Tropics with Numerical Weather Prediction and Machine Learning.

[BibT_eX]

[DOI]

Nigel Yuan Yun Ng

Harish Gopalan

Venugopalan S. G. Raghavan

Chin Chun Ooi

Proceedings of the 17th International Conference on Control, 2022

Automated Quantification of Traffic Particulate Emissions via an Image Analysis Pipeline.

[BibT_eX]

[DOI]

Proceedings of the 17th International Conference on Control, 2022

2021

Model-Agnostic Hybrid Numerical Weather Prediction and Machine Learning Paradigm for Solar Forecasting in the Tropics.

[BibT_eX]

[DOI]

Nigel Yuan Yun Ng

Harish Gopalan

Venugopalan S. G. Raghavan

Chin Chun Ooi

CoRR, 2021

CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method.

[BibT_eX]

[DOI]

CoRR, 2021

U-Net-Based Surrogate Model For Evaluation of Microfluidic Channels.

[BibT_eX]

[DOI]

Quang Tuyen Le

Pao-Hsiung Chiu

Chinchun Ooi

CoRR, 2021

Surrogate Modeling of Fluid Dynamics with a Multigrid Inspired Neural Network Architecture.

[BibT_eX]

[DOI]

Quang Tuyen Le

Chin Chun Ooi

CoRR, 2021

Improved Surrogate Modeling of Fluid Dynamics with Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2021

Chin Chun Ooi

Timeline

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Bibliography

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