Physical AI: robots, scientific computing, and digital twins
Justin Hodges, PhDRead what I read, code what I code. I share lots of papers/code for topics in artificial intelligence/machine learning applied to engineering (CFD, FEA, numerical methods, aerodynamics, turbulence modeling, & more). I will publish enough to keep you busy.
| Platform |  | Pricing | Freemium | Publishes | Daily |
|---|---|---|---|---|---|
| Issues | 117 | Founded | 2 years ago | Last Issue | 7 days ago |
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hodgesj.substack.comLatest Issues
Physics Transformer on DrivAerML
Tutorial code for automotive aerodynamics
This is a beginner-friendly, from-scratch PyTorch tutorial based on Physics Transformer: Tailoring Transformer for General PDE Prediction (Sun et al., arXiv v1, 2026). Super fun! I’ll check back ev...
Robotics News & Literature (August 31st)
The August 22 issue focused on evidence infrastructure: the artifacts that let people inspect, compare, and challenge a robotics claim. This week, that evidence gathered around thresholds, including how little demonstration data can specify...
Physics AI/ML Literature Review: July 21-August 23, 2026
Company updates first, then papers. PDFs linked.
Updates, Notes, and Happenings in the Commercial Space
Robotics News & Literature (August 24th)
Another Fine Grasp
Robotics news (part 1) and companion literature (part 2, bottom).
The August 3 issue ended with operational authority: who permits a robot to act, what evidence earns that permission, and how it can be withdrawn. Over...
What “HelloWorld” Teaches Us About Interactive Video World Models
Code tutorial and summary
A technical review of Ouyang, Liu, Chu, Zhang & Sato, “HelloWorld: Enabling Socially Interactive Characters in Video World Models” — written for researchers from mechanical, aerospace, and simulation-heavy backgro...
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Authors
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\ud83d\udc4b Hello. My name is Justin and I am head of physical ai at CoreWeave. Read what I read - code what I code. I love applying #ai and #machinelearning to #engineering and scientific simulation.
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