28 citations · 46 across the 5 of their papers we have counts for
8 papers
HypergraphFormer: Learning Hypergraphs from LLMs for Editable Floor Plan Generation
Nikita Klimenko, Hesam Salehipour, Parham Eftekhar +2
In this work, we propose HypergraphFormer, a novel and efficient approach to floor plan generation based on learning hypergraph representations with a large language model (LLM). T…
Simulating The Urban Canopy's Impact on Wind-Driven Natural Ventilation
Nicholas Bachand, Hesam Salehipour, Catherine Gorle
The urban canopy affects wind in complex ways, making it challenging to predict wind-driven natural ventilation and cooling in buildings. Using large eddy simulations of coupled ou…
Physics-informed Reduced Order Modeling of Time-dependent PDEs via Differentiable Solvers
Nima Hosseini Dashtbayaz, Hesam Salehipour, Adrian Butscher +1
Reduced-order modeling (ROM) of time-dependent and parameterized differential equations aims to accelerate the simulation of complex high-dimensional systems by learning a compact…
Optimal Design of Vehicle Dynamics Using Gradient-Based, Mixed-Fidelity Multidisciplinary Optimization
Hyunmin Cheong, Mehran Ebrahimi, Hesam Salehipour +2
In automotive engineering, designing for optimal vehicle dynamics is challenging due to the complexities involved in analysing the behaviour of a multibody system. Typically, a sim…
Reduced-order modeling of unsteady fluid flow using neural network ensembles
Rakesh Halder, Mohammadmehdi Ataei, Hesam Salehipour +2
The use of deep learning has become increasingly popular in reduced-order models (ROMs) to obtain low-dimensional representations of full-order models. Convolutional autoencoders (…
XLB: A differentiable massively parallel lattice Boltzmann library in Python
Mohammadmehdi Ataei, Hesam Salehipour
The lattice Boltzmann method (LBM) has emerged as a prominent technique for solving fluid dynamics problems due to its algorithmic potential for computational scalability. We intro…