Discovery Lab is a collaboration between the Vrije Universiteit Amsterdam, the University of Amsterdam and Elsevier. The lab’s philosophy is to drive scientific discovery using machine intelligence. The researchers study and develop technology, infrastructure and methods to support the current transformation of science. They focus on data-driven activity, where scientists increasingly rely on intelligent tooling for searching and reading scientific literature, to formulate hypotheses, and to interpret data.
A selection of research Topics
The lab seeks to advance the ability to construct, use and study large-scale knowledge graphs that integrate knowledge across heterogeneous scientific content and data.
The lab investigates the use of reinforcement learning to work with structured multi-modal information such as user context, knowledge graphs, or text as inputs.
The lab focusses on challenging scenarios that require question answering models to reason, gather, and synthesize disjoint pieces of information, within context, to generate an answer.
Elsevier is a global information analytics business that helps scientists and clinicians to find new answers, reshape human knowledge, and tackle the most urgent human crises. For 140 years, they have partnered with the research world to curate and verify scientific knowledge. Today, they’re committed to bringing that rigor to a new generation of Elsevier platforms. Their applications put users in control and enable faster, more efficient ways of working, freeing up users to focus on their goals.
Frank van Harmelen
Paul Groth is a professor of algorithmic data science at the University of Amsterdam.
Frank van Harmelen is a professor in knowledge representation & reasoning at the Vrije Universiteit Amsterdam.
Rinke Hoekstra is lead architect in technology at Elsevier.
Michael Cochez is an assistant professor artificial intelligence at the Vrije Universiteit Amsterdam.
Philip Tillman is a senior machine learning scientist at Elsevier.