MMag. Dr.

Doris Gruber


Doris Gruber is a member of the research unit Digital Historiography and Editions, since July 2022 as part of the project Ottoman Nature in Travelogues, 1501–1850: A Digital Analysis (ONiT) funded by the Austrian Science Fund (FWF).

Brief Biography

Doris Gruber studied history and art history at the University of Graz and at Sciences Po Paris. In 2018, she completed her PhD with honours at the University of Graz. The Gerda Henkel Foundation (Düsseldorf) as well as well as the Prussian Cultural Heritage Foundation (Berlin) supported the creation of the thesis, for which Doris Gruber received the Anniversary Prize of the Böhlau Verlag, Vienna and the Francis Stephen Award. Together with her colleagues from the Travelogues-project she received the Lee Dirks Award for Best Full Research Paper at the iConference 2020 in Borås (Sweden).

Since completing her doctorate, Doris Gruber held a scholarship at the Herzog August Library in Wolfenbüttel (spring 2022), was a senior researcher at the Paris Lodron University Salzburg (2020–2022), and part of the Travelogues-project funded by the Austrian Science Fund (FWF) and the German Research Foundation (DFG) at the research unit (2018–2021). Since 2020, she has also been teaching at the University of Vienna. During her undergraduate and graduate studies, she had various part-time jobs and internships, including at the House of History Baden-Württemberg in Stuttgart, the Belvedere in Vienna and the Styrian State Archives in Graz.

Research Interests

Period: early modern era
Area: Holy Roman Empire, Habsburg Monarchy, Ottoman Empire
Topics: history of knowledge and science, media and book history, digital humanities, travel literature, text–image relations, machine learning, comets

Selected Publications





TRAVELOGUES (completed)


with Arno Strohmeyer (ed.): On the Way to the (Un)known? The Ottoman Empire in Travelogues (c. 1450–1900)


Frühneuzeitlicher Wissenswandel


(with J. Rörden, M. Krickl and B. Haslhofer), Identifying Historical Travelogues in Large Text Corpora Using Machine Learning, pp. 801–815