Ehsan Haghighat

Ehsan Haghighat

Researcher in Scientific Computations, Stochastic Modeling, and Deep Learning


Massachusetts Institute of Technology


I am a researcher and practitioner in the areas of Scientific Machine Learning, Computational Mechanics, and Mechanics of Solids and Porous Media. My research interests include computational modeling and uncertainty quantification of engineering systems, and the use of artificial intelligence tools, including deep learning, in engineering analysis. I am currently a research scientist at Carbon Inc., working on modeling and optimization of lattice structures using FEM and DL methods.


  • Scientific Machine Learning
  • Stochastic Modeling and Uncertainty Quantification
  • Numerical Methods
  • Mechanics of Solids and Porous Media


  • Postdoctoral Fellow, 2020-2021

    University of British Columbia

  • Postdoctoral Associate, 2017-2020

    Massachusetts Institute of Technology

  • PhD in Computational Mechanics, 2011-2015

    McMaster University

Recent Publications



Research Scientist - Computational Geometry

Carbon, Inc.

Jan 2022 – Present San Francisco, CA, USA

Research and development:

  • Computational modeling of lattice structures
  • Physics-informed deep learning
  • Computational geometry Skills:
  • C++, Python, TensorFlow, AWS, HPC.

Data Scientist

Geotab, Inc.

Sep 2021 – Jan 2022 Burnaby, BC, Canada

Research and development:

  • Big-data analytics
  • Geospatial data analysis Skills:
  • SQL, BigQuery, GCP, Python, SciPy.

Simulation Consultant

Seismix Reservoir Management, LLC

Jan 2020 – Present Cambridge MA, USA

Research activities include:

  • Stochastic modeling
  • Uncertainty quantification
  • Multiphase flow simulations Skills:
  • Python, HPC, UQ, Big-data, visualization.

Postdoctoral Fellow

University of British Columbia

Jan 2020 – May 2021 Vancouver BC, CA

Research activities include:

  • Deep learning for engineering
  • Stochastic modeling
  • Uncertainty quantification Skills:
  • Python (TensorFlow, Keras, SciPy, Numpy, Viz).

Postdoctoral Associate

Massachusetts Institute of Technology

Jan 2017 – Dec 2019 Cambridge MA, US

Research activities include:

  • Assessment of induced seismicity through multiphase flow and geomechanics simulations
  • Development of MATLAB’s vFEMLab for geological modeling using implicit interface methods
  • Development of SciANN library for Physics-Informed Deep Learning
  • Stochastic modeling of gas leakage to the surface Skills:
  • Python (TensorFlow, Keras, SciPy, Numpy, Viz), C++.

Lead Mechanics

Forming Technologies Inc.

Oct 2014 – Dec 2016 Burlington ON, Canada

Research and development activities included:

  • Development of a new implicit-incremental FEM solver using thick shell theory with large-deformation and contact considerations.
  • Development and exploration of various linear system solvers.

Research Assistant and Graduate Student

McMaster University

Jul 2011 – Dec 2014 Hamilton ON, Canada

Study and research activities included:

  • Constitutive modeling
  • FEM, XFEM, Meshfree
  • Scientific computations and linear algebra
  • Programming, C++, FORTRAN, Python, MATLAB.



ML for engineering and science applications.


A Keras wrapper for scientific computations and physics-informed deep learning using artificial neural networks


A vectorized FEM MATLAB library using the implicit interface methods


A proposal for a recommendation system for learning taste profile (3rd place winner).