activity
20202025
most citedData-assisted combustion simulations with dynamic submodel assignment using random forests

44 citations · 83 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2025

Opportunistic Expert Activation: Batch-Aware Expert Routing for Faster Decode Without Retraining

Costin-Andrei Oncescu, Qingyang Wu, Wai Tong Chung +5

An increasing number of LLMs employ Mixture-of-Experts (MoE) architectures where the feed-forward layer is replaced by a pool of experts and each token only activates a small subse…

cs.LG2024

A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport

M. Giselle Fernández-Godino, Wai Tong Chung, Akshay A. Gowardhan +4

High-resolution spatiotemporal simulations effectively capture the complexities of atmospheric plume dispersion in complex terrain. However, their high computational cost makes the…

cs.LG2023★ 7 cited

Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data

Wai Tong Chung, Bassem Akoush, Pushan Sharma +9

Analysis of compressible turbulent flows is essential for applications related to propulsion, energy generation, and the environment. Here, we present BLASTNet 2.0, a 2.2 TB networ…

cs.LG2022★ 1 cited

The Bearable Lightness of Big Data: Towards Massive Public Datasets in Scientific Machine Learning

Wai Tong Chung, Ki Sung Jung, Jacqueline H. Chen +1

In general, large datasets enable deep learning models to perform with good accuracy and generalizability. However, massive high-fidelity simulation datasets (from molecular chemis…

physics.flu-dyn2021★ 31 cited

Interpretable Data-driven Methods for Subgrid-scale Closure in LES for Transcritical LOX/GCH4 Combustion

Wai Tong Chung, Aashwin Ananda Mishra, Matthias Ihme

Many practical combustion systems such as those in rockets, gas turbines, and internal combustion engines operate under high pressures that surpass the thermodynamic critical limit…

physics.flu-dyn2020★ 44 cited

Data-assisted combustion simulations with dynamic submodel assignment using random forests

Wai Tong Chung, Aashwin Ananda Mishra, Nikolaos Perakis +1

In this investigation, we outline a data-assisted approach that employs random forest classifiers for local and dynamic combustion submodel assignment in turbulent-combustion simul…