AI in Engineering, Physics, Aerodynamics

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Mechanical, chemical, aerospace, civil, and other engineers — this is your place to build up your skills with AI/ML, specific to engineering domains. There are tons of generic resources, but when you filter out only those that focus on our engineering problems, only a fraction remain. After writing a book on this topic, I decided to follow-up with a Substack page.

Sample posts:October 21st: Job Postings for AI/ML in EngineeringLibrary for Data-Driven Physics Simulation Lectures (Free, on-demand)Install-Free Code Tutorial: PINNs in turbulent flowPromising AI Foundation Models in Science: Examples with Code and Data

Sample posts:

October 21st: Job Postings for AI/ML in Engineering

Library for Data-Driven Physics Simulation Lectures (Free, on-demand)

Install-Free Code Tutorial: PINNs in turbulent flow

Promising AI Foundation Models in Science: Examples with Code and Data

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The mantra I strive to sustain for my newsletter is to ‘read what I read - code what I code’. I love applying ai and machine learning to engineering and scientific simulation, and as well on physics measurement and testing data.

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