Ehsan Haghighat is an AI Scientist and computational engineer with eight years of experience developing deep learning and scientific computing solutions for complex physical systems. He combines a strong academic foundation (PhD) and postdoctoral research at MIT and UBC with industry leadership roles—most recently heading ML and simulation teams and now at UniversalAGI—bridging numerical methods, SciML, and uncertainty quantification. His technical toolkit spans Python, TensorFlow/PyTorch, C++, HPC/OpenMPI and cloud platforms, applied to PDE/ODE solvers, geomechanics and metamaterials simulation. Ehsan has repeatedly translated research into production: building cloud-distributed stochastic modeling frameworks, accelerating 3D simulation with ML, and leading assembly/motion planning model development. He publishes on ML for engineering infrastructure (Google Scholar) and brings a rare blend of hands-on solver development, data-driven modeling, and operational deployment. Based in Vancouver, he pairs deep mechanics instincts with practical engineering to tame uncertainty in large-scale physical systems.
8 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Engineering, Doctor of Philosophy (Ph.D.), Engineering at McMaster University
Master's Degree, Engineering, Master's Degree, Engineering at Sharif University of Technology
Contributions:32 commits, 29 PRs, 8 pushes in 2 years 10 months
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