Christian Dallago

Academic title

Dr. Rer. Nat.

Current role

Senior Solution Architect - Healthcare and Life Sciences, EMEA


(long, 110 words)

Chris is a computer scientist turned bioinformatician with a passion for systematically modelling biological mechanisms through machine learning. His path towards reaching this goal led him to contribute and push the community of learned protein sequence representations in order to find new, principled ways to describe biological entities. Bio-sequence representation learning, for instance through transformer models, is today an established field in bioinformatics with flourishing frameworks and impactful research applications, like the prediction of protein 3D structure from just an input sequence. Chris remains focused on trying to address problems for which data and intuition remain scarce, for instance those allowing to design new proteins with therapeutic or industrial use.

(short, 35 words)

Chris, a computer scientist turned bioinformatician, passionately models biological mechanisms using machine learning. He's advanced bio-sequence representation learning, contributing to its establishment, notably in transformer models. Chris is dedicated to solving scarce data problems, such as designing proteins for therapeutic and industrial applications.