Andreas Loukas

Prescient Design, Genentech, Roche

Andreas is a computer science researcher and graph enthusiast. His work focuses on the foundations and applications of machine learning to structured problems. He aims to find ways to exploit (graph, constraint, group) information, with the ultimate goal of designing algorithms that can learn from fewer data. He is also fascinated by the theoretical analysis of neural networks and in using them to solve hard combinatorial and bio-engineering problems (especially protein design).