Uploaded November 2025 | Updated September 2026, 1 week ago
Explore NarniaLabs: narnia.ai
Connect with Namwoo on LinkedIn: linkedin.com/in/namwoo-kang-79347386
In this deep-dive masterclass, Professor Namwoo Kang of the KAIST Smart Design Lab and co-founder of Narnia Labs breaks down how AI is transforming design optimization, solving problems that traditional simulation and surrogate-based optimization can’t handle.
He explains why real industrial design problems are high-dimensional, why classical parameterization methods fail, and how generative AI, predictive AI, and optimization AI work together in a unified framework to reduce design complexity through latent-space optimization.
Through a detailed case study on automotive wheel design, Namwoo shows:
- How AI automatically extracts shape features
- Why dimensionality reduction is the key to fast, robust optimization
- How 2D → 3D reconstruction enables photorealistic and engineering-valid designs
- How synthetic CAD data + deep learning enable accurate stress prediction
- How domain adaptation solves “new product” prediction failures
- How implicit neural representations enable true 3D optimization with minimal data
This is one of the clearest explanations of AI-enabled engineering design, showing real applications, real challenges, and real solutions used by KAIST and Narnia Labs today.
ONLINE PRESENCE
================
🌍 My website - jousefmurad.com
💌 My weekly science newsletter - jousef.substack.com
📸 Instagram - instagram.com/jousefmrd
🐦 Twitter - https://x.com/Jousefm2
CONTACT:
————————
If you need help or have any questions or want to collaborate feel free to reach out to me via email: support@jousefmurad.com
#ai
#designoptimization
#cad
Disclaimer: Some of these links are affiliate links that make me earn a small commission when you make a purchase at no additional cost.
Deep Dive Recorded: Nov, 18th, 2025 - Subscriber Release Count: 43,808
Explore NarniaLabs: narnia.ai
Connect with Namwoo on LinkedIn: linkedin.com/in/namwoo-kang-79347386
In this deep-dive masterclass, Professor Namwoo Kang of the KAIST Smart Design Lab and co-founder of Narnia Labs breaks down how AI is transforming design optimization, solving problems that traditional simulation and surrogate-based optimization can’t handle.
He explains why real industrial design problems are high-dimensional, why classical parameterization methods fail, and how generative AI, predictive AI, and optimization AI work together in a unified framework to reduce design complexity through latent-space optimization.
Through a detailed case study on automotive wheel design, Namwoo shows:
- How AI automatically extracts shape features
- Why dimensionality reduction is the key to fast, robust optimization
- How 2D → 3D reconstruction enables photorealistic and engineering-valid designs
- How synthetic CAD data + deep learning enable accurate stress prediction
- How domain adaptation solves “new product” prediction failures
- How implicit neural representations enable true 3D optimization with minimal data
This is one of the clearest explanations of AI-enabled engineering design, showing real applications, real challenges, and real solutions used by KAIST and Narnia Labs today.
ONLINE PRESENCE
================
🌍 My website - jousefmurad.com
💌 My weekly science newsletter - jousef.substack.com
📸 Instagram - instagram.com/jousefmrd
🐦 Twitter - https://x.com/Jousefm2
CONTACT:
————————
If you need help or have any questions or want to collaborate feel free to reach out to me via email: support@jousefmurad.com
#ai
#designoptimization
#cad
Disclaimer: Some of these links are affiliate links that make me earn a small commission when you make a purchase at no additional cost.
Deep Dive Recorded: Nov, 18th, 2025 - Subscriber Release Count: 43,808
