Thomas Heinis Keynote Speaker

Professor Thomas Heinis is a computer scientist at Imperial College London whose work sits at the intersection of artificial intelligence, large-scale data systems and next-generation computing infrastructure. He leads the SCALE Lab at Imperial, where his research explores how we store, retrieve and analyse data efficiently enough to power the next wave of AI and scientific discovery.

His expertise spans AI-ready data systems, learned indexes, large-scale analytics, scientific data management, and DNA-based data storage. This gives him a distinctive perspective on a question increasingly central to business and government alike: not just how AI models work, but what infrastructure is required to make AI usable, scalable and sustainable in practice.

Before joining Imperial, Thomas Heinis earned his PhD and MSc in Computer Science from ETH Zurich and was a Postdoctoral Fellow at EPFL Lausanne. His research has addressed some of the most demanding data challenges in science, from neuroscience and simulation to molecular storage and machine learning–driven systems design.

A widely published academic and international keynote speaker, he has spoken on topics including synthetic DNA for storing and processing data, learned indexes for streaming data, and the challenges of managing complex, high-volume information at scale. For audiences seeking substance beyond AI buzzwords, Thomas Heinis offers a rare blend of technical depth, interdisciplinary insight and strategic clarity on where AI is going next — and what it will take to support it.