Recent News

Physics-informed neural networks for solid mechanics

  • [Feb 19, 2021] Ehsan Haghighat's paper in collaboration with Maziar Raissi from University of Colorado Boulder and Hector Gomez from Purdue University, on a physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics, published in CMAME. (Read the paper)

Chemotaxis in porous media

AGU Fall Meeting

Hydrate crustal fingering

Physics-informed neural networks

  • [Nov 26, 2020] Ehsan Haghighat's paper, on SciANN: A Keras/TensorFlow wrapper for scientific computations and physics-informed deep learning using artificial neural networks, published in CMAME. (Read the paper)

Multiphase flow and granular mechanics

Constant-rate imbibition



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