Jian Cheng Wong

Orcid: 0000-0002-3215-1888

According to our database¹, Jian Cheng Wong authored at least 34 papers between 2011 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Links

On csauthors.net:

Bibliography

2026

AI-Driven Performance-to-Design Generation and Optimization of Marine Propellers.

[BibT_eX]

[DOI]

CoRR, April, 2026

Agentic AI-Enabled Framework for Thermal Comfort and Building Energy Assessment in Tropical Urban Neighborhoods.

[BibT_eX]

[DOI]

CoRR, April, 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

Landscape-aware Automated Algorithm Design: An Efficient Framework for Real-world Optimization.

[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

2025

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

[BibT_eX]

[DOI]

CoRR, January, 2025

Evolvable Conditional Diffusion.

[BibT_eX]

[DOI]

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

2024

Data-driven surrogate modelling of residual stresses in Laser Powder-Bed Fusion.

[BibT_eX]

[DOI]

Lucas Lestandi

Jian Cheng Wong

Guoying Dong

Shemuel Joash Kuehsamy

Int. J. Comput. Integr. Manuf., June, 2024

Learning in Sinusoidal Spaces With Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Artif. Intell., March, 2024

Fourier warm start for physics-informed neural networks.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 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

Soft Constraint in Local Structure Approximation-PINN.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Artificial Intelligence, 2024

Differentiable Hash Encoding for Physics-Informed Neural Networks.

[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

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

2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Can Transfer Neuroevolution Tractably Solve Your Differential Equations?

[BibT_eX]

[DOI]

Jian Cheng Wong

Abhishek Gupta

Yew-Soon Ong

IEEE Comput. Intell. Mag., 2021

2015

Reducing False Arrhythmia Alarms in the ICU.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2015

2011

Comparing the Macroeconomic Responses of US and Japan through Time Series Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2011

Time Series Segmentation as a Discovery Tool - A Case Study of the US and Japanese Financial Markets.

[BibT_eX]

Proceedings of the KDIR 2011, 2011

Jian Cheng Wong

Timeline

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On csauthors.net:

Bibliography

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