4 citations · 13 across the 6 of their papers we have counts for
6 papers
RE-LLM: Integrating Large Language Models into Renewable Energy Systems
Ali Forootani, Mohammad Sadr, Danial Esmaeili Aliabadi +1
Energy system models are increasingly employed to guide long-term planning in multi-sectoral environments where decisions span electricity, heat, transport, land use, and industry.…
Climate Aware Deep Neural Networks (CADNN) for Wind Power Simulation
Ali Forootani, Danial Esmaeili Aliabadi, Daniela Thraen
Wind power forecasting plays a critical role in modern energy systems, facilitating the integration of renewable energy sources into the power grid. Accurate prediction of wind ene…
Bio-Eng-LMM AI Assist chatbot: A Comprehensive Tool for Research and Education
Ali Forootani, Danial Esmaeili Aliabadi, Daniela Thraen
This article introduces Bio-Eng-LMM AI chatbot, a versatile platform designed to enhance user interaction for educational and research purposes. Leveraging cutting-edge open-source…
GS-PINN: Greedy Sampling for Parameter Estimation in Partial Differential Equations
Ali Forootani, Harshit Kapadia, Sridhar Chellappa +2
Partial differential equation parameter estimation is a mathematical and computational process used to estimate the unknown parameters in a partial differential equation model from…
GN-SINDy: Greedy Sampling Neural Network in Sparse Identification of Nonlinear Partial Differential Equations
Ali Forootani, Harshit Kapadia, Sridhar Chellappa +2
The sparse identification of nonlinear dynamical systems (SINDy) is a data-driven technique employed for uncovering and representing the fundamental dynamics of intricate systems b…
A Robust SINDy Approach by Combining Neural Networks and an Integral Form
Ali Forootani, Pawan Goyal, Peter Benner
The discovery of governing equations from data has been an active field of research for decades. One widely used methodology for this purpose is sparse regression for nonlinear dyn…