121 citations · 330 across the 20 of their papers we have counts for
20 papers
(HB-ARFM) History-Bootstrapped Flow Matching for Inverse Boiling Reconstruction
Xianwei Zou, Sheikh Md Shakeel Hassan, Arthur Feeney +1
Reconstructing spatiotemporal fields from partial observations is fundamental to scientific inference, from inferring atmospheric states from satellite data to recovering fluid sta…
NUCLEUS-MoE: Unified Model of Pool Boiling for Liquid Cooling
Arthur Feeney, Xianwei Zou, Sheikh Md Shakeel Hassan +2
Two-phase boiling enables heat transfer rates an order of magnitude higher than single-phase cooling, but it remains difficult to model due to the strong coupling between phase cha…
EventFlow: Real-Time Neuromorphic Event-Driven Classification of Two-Phase Boiling Flow Regimes
Sanghyeon Chang, Srikar Arani, Nishant Sai Nuthalapati +7
Flow boiling is an efficient heat transfer mechanism capable of dissipating high heat loads with minimal temperature variation, making it an ideal thermal management method. Howeve…
Bubbleformer: Forecasting Boiling with Transformers
Sheikh Md Shakeel Hassan, Xianwei Zou, Akash Dhruv +2
Modeling boiling (an inherently chaotic, multiphase process central to energy and thermal systems) remains a significant challenge for neural PDE surrogates. Existing models requir…
Mondrian: Transformer Operators via Domain Decomposition
Arthur Feeney, Kuei-Hsiang Huang, Aparna Chandramowlishwaran
Operator learning enables data-driven modeling of partial differential equations (PDEs) by learning mappings between function spaces. However, scaling transformer-based operator mo…
Fused3S: Fast Sparse Attention on Tensor Cores
Zitong Li, Aparna Chandramowlishwaran
Sparse attention is a core building block in many leading neural network models, from graph-structured learning to sparse sequence modeling. It can be decomposed into a sequence of…