Training AI Models for Engineering, Autodesk Alias & Free Course on Physics-Driven Generative Design
📚 Not AI will substitute you, but someone using AI will.
It’s been a while!
It’s been a while since my last newsletter, so I wanted to briefly reconnect and share what’s been happening behind the scenes.
Over the past few months, I’ve shifted much of my focus to APEX, where my team and I are currently building automation systems and practical AI solutions for businesses. Much of my time has gone into developing workflows, testing agent-based setups, and helping companies turn AI from a buzzword into something that actually saves time and drives revenue.
We’re living in a unique moment where AI, automation, and intelligent agents are moving from experimentation to real business infrastructure. Because of that, I plan to share more insights, lessons, and concrete use cases in this space going forward.
If you’re exploring automation, AI agents, or simply wondering what this could look like inside your business, feel free to reach out. I’m always happy to exchange ideas or point you in the right direction.
💻 Connected Design & Visualization in Autodesk Alias - Barry Kimball and Jakob Lohse | Deep Dive
🧠 Free Engineering Course on Physics-Driven Generative Design for Thermal Systems
Join ToffeeX for a 4‑part live masterclass on physics‑driven generative design.
Over four weeks and four episodes, they will walk through the complete workflow for a liquid‑cooled heat sink: from CAD setup to optimisation and CFD validation.
👉 Why this series, why now?
Most “generative design” content is either marketing fluff or black‑box magic. With ToffeeX we’re doing something different:
• Physics‑driven, not guess‑driven: full Multiphysics optimization, not AI shape guesses.
• Explainable: you control objectives, constraints and outcomes.
• Manufacturing‑aware: constraints for AM and conventional processes are built into the optimization.
💻 How do you train AI models when real simulation data is scarce or expensive?
💦 Machine Learning in Fluid Dynamics
A curated list of awesome Machine Learning (Deep Learning) projects in Fluid Dynamics. Topics consist of Computational Fluid Dynamics (CFD), turbulence modeling, non-Newtonian fluids, Hemodynamics, PIV measurement, Geophysical fluid dynamics, Aeroelasticity, multiphase flow, etc.
♨️ Fluid Mechanics Series
This collection of videos was created about half a century ago to explain fluid mechanics in an accessible way for undergraduate engineering and physics students. I find that no other series of videos has explained the basics of fluid mechanics better than this one by the National Committee for Fluid Mechanics (those national committees gotta be good for something...)
📚 Book of the Week
An Introduction to Computational Fluid Dynamics
This book is a guide to numerical methods for solving fluid dynamics problems. It describes in detail the most widely used discretization and solution methods, which are also found in most commercial CFD programs. It also covers some advanced topics, like moving grids, simulation of turbulence, computation of free-surface flows, multigrid methods, and parallel computing. Since CFD is a very broad field, we provide fundamental methods and ideas, with some illustrative examples, upon which more advanced techniques are built.
💻 Engineering Tool of the Week – FeenoX
FeenoX can be seen either as
a syntactically-sweetened way of asking the computer to solve engineering-related mathematical problems, and/or
a finite-element(ish) tool with a particular design basis.
Let’s connect on Instagram or LinkedIn!
For any business-related issues or collaborations, email me at support@jousefmurad.com!
Keep engineering your mind! 🧠
Jousef