We're thrilled to announce that Max Welling will be joining us for an AMA on Wednesday April 15th from 17:00 to 18:30 CEST (11am - 12:30pm EDT)
Who is Max Welling?
Max Welling is an ML researcher whose career has spanned academia, big tech and life as a founder -- most recently working on ML for physical and scientific systems. Over the past few years he's moved from "classical" ML work like GNNs, Bayesian Deep Learning, CNNs) into AI for science and materials, including time on Microsoft's earth modelling system Aurora.
He is also the co-founder of CuspAI, where they're currently building a "search engine" for next generation materials. In practice, their work focuses both on building AI systems that are able to search extremely messy, high-dimensional spaces and propose new materials with specific properties, and dealing with the gaps arising between models/data, and the real world.
He will host an AMA at the time specified above, and will be delighted to discuss the intersection of AI and Materials Science with us.
Here is a selection of topics he'd like to go deep on:
- ML Architectures that work in noisy, sparse, and only partially observable environments
- Science not just as a "use case" for AI, but as a fundamental layer of the infrastructure
- AI4Science in general, focusing on cases like Foundation Models vs domain-specific approaches (what works, what's hype, what's real?
- "Physical AI" as in treating experiments and lab loops as part of the computation, not just downstream validation. (Like treatign the physical world as a live data-generator for frontier model training
- The hardest unsolved problems at the interface of ML & Science (Data quality, synthesizability, deployment)
- Human-in-the-loop systems and how to ensure model output reliability
- ML Career advice (Why he focused his work on problems with the potential for big societal impacts like carbon capture, energy materials & compute efficiency)
His main aim will be to connect with the community & to share some of his knowledge and expertise.
He's provided proof via twitter here:
https://x.com/wellingmax/status/2042678504316141765
His most impactful contributions include, among others:
Semi-Supervised Classification with Graph Convolutional Networks
Auto-Encoding Variational Bayes
Bayesian Learning via Stochastic Gradient Langevin Dynamics
Equivariant Diffusion for Molecule Generation in 3D
Aurora: A Foundation Model for the Earth System
Make sure to think of interesting questions & drop them in the comments below we'll merge them with the AMA thread on Wednesday, thank you!
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