Georgios Tritsaris

My current focus is on applying artificial intelligence, particularly deep learning architectures, to accelerate scientific discovery and technology development. I have led research and development in academia and industry for energy, mobility and electronics, domains which, in turn, push the frontier of artificial intelligence.

Starting from novel concepts, models, and methods to understand how nature works and how everything is connected, I then apply this knowledge to design materials, devices, and systems that make the air cleaner, electric vehicles go further safely, and computing more powerful and useful. I develop people and ventures, and champion policies that enable others to join and scale this work.

My scientific research lies at the intersection of physics, materials, and computation, with a focus on obtaining new insights into the physical processes that govern scientifically and technologically interesting structures. The main idea is to systematically increase our knowledge of matter across spatiotemporal scales by using supercomputers and intelligent algorithms to conduct informative virtual experiments and generate high-fidelity datasets.

My engineering and technology work focuses on translating this scientific understanding into useful processes and products, with emphasis on modularity, performance, and scale. This is often pursued by building self-improving systems that integrate physics-based simulation, data-driven models, and real-time feedback to adaptively operate in physical and virtual environments, such as AI agents for materials screening and battery digital twin.