Rens Bod

Rens Bod is professor of Digital Humanities and History of Humanities, director of the Center for Digital Humanities and director of the Vossius Center for the History of Humanities and Sciences. He investigates the humanities from both computational and historical perspectives. He currently serves as president of the Society for the History of the Humanities, and is a member of Royal Dutch Society of Sciences and Humanities (“Koninklijke Hollandsche Maatschappij der Wetenschappen”) and of the Society for the Dutch Letters (“Maatschappij der Nederlandse Letterkunde”). He is also the founder of WOinActie, an action group that aims at achieving appropriate funding for Dutch universities.

Bod is the author of the first historical overview of the humanities from Antiquity to the present: A New History of the Humanities (translated from the Dutch "De Vergeten Wetenschappen"). The book has appeared in 7 translations, and was voted as best science book of 2011 by Kennislink and as one of the 25 books on science you "must have read" by NRC Handelsblad. The book has been reviewed by over 45 journals and newspapers and is acclaimed as "an extraordinarily ambitious undertaking ... the first ever history of its kind" (Times Literary Supplement) and "Bod takes the humanities back to their rightful place in the family tree of science."

Recently, Rens Bod has also published a monograph on the general history of knowledge disciplines, entitled Een Wereld Vol Patronen: De Geschiedenis van Kennis ("A World of Patterns: The History of Knowledge"), which explores the search for patterns and underlying principles in 20 disciplines from 5 continents across the sciences, social sciences and the humanities. The book will soon appear in English.

Bod's computational work covers natural language processing, computational musicology, digital aesthetics and computational literary studies. In the field of digital humanities, he coordinates several public-private partnerships in the humanities. He is one of the main architects of the Data-Oriented Parsing model, a general machine learning technique that creates rule-like behavior without rules, and which has been applied to language, music, vision and reasoning.