most citedDoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations

2 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

physics.ins-det2026

Agentic TCAD Calibration Workflow for Oxide Semiconductor Transistors

Gyujun Jeong, Junmo Lee, Sungwon Cho +11

Experimental TCAD calibration is essential for predictive technology modeling of emerging oxide semiconductor transistors. However, it remains time-consuming and expert dependent b…

cs.LG2026

Physics-informed AI Accelerated Retention Analysis of Ferroelectric Vertical NAND: From Day-Scale TCAD to Second-Scale Surrogate Model

Gyujun Jeong, Sungwon Cho, Minji Shon +13

Ferroelectric field-effect transistors (FeFET)-based vertical NAND (Fe-VNAND) has emerged as a promising candidate to overcome z-scaling limitations with lower programming voltages…

cs.LG2025

GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer

Corey Adams, Rishikesh Ranade, Ram Cherukuri +1

We present GeoTransolver, a multiscale geometry-aware physics attention transformer for Computer Aided Engineering (CAE). GeoTransolver extends the Transolver backbone with GALE (G…

cs.LG2025

Automotive Crash Dynamics Modeling Accelerated with Machine Learning

Mohammad Amin Nabian, Sudeep Chavare, Deepak Akhare +3

Crashworthiness assessment is a critical aspect of automotive design, traditionally relying on high-fidelity finite element (FE) simulations that are computationally expensive and…

physics.geo-ph2025

Data-driven solar forecasting enables near-optimal economic decisions

Zhixiang Dai, Minghao Yin, Xuanhong Chen +27

Solar energy adoption is critical to achieving net-zero emissions. However, it remains difficult for many industrial and commercial actors to decide on whether they should adopt di…

cs.LG2025

A Benchmarking Framework for AI models in Automotive Aerodynamics

Kaustubh Tangsali, Rishikesh Ranade, Mohammad Amin Nabian +5

In this paper, we introduce a benchmarking framework within the open-source NVIDIA PhysicsNeMo-CFD framework designed to systematically assess the accuracy, performance, scalabilit…

cs.LG2025★ 2 cited

DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations

Rishikesh Ranade, Mohammad Amin Nabian, Kaustubh Tangsali +4

Numerical simulations play a critical role in design and development of engineering products and processes. Traditional computational methods, such as CFD, can provide accurate pre…