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Cambridge Digital Humanities


Dr Julie Blake

Julie’s PhD research uses a mixed methods – digital and material, quantitative and qualitative – approach to understanding the nature of poetry and poetry anthologies in the school English curriculum. During the Methods Fellowship she will be co-developing a digital pedagogy project with scholars from the Centre for Research in Children’s Literature at Cambridge, provisionally titled “Bug Hunt”. Researchers with interests in children’s literature and the history of science will be invited to experiment with digital methods for exploring the representation of insects in nineteenth-century books written for children.



Mary Chester-Kadwell​

Mary is a Senior Software Developer at Cambridge University Library and works on Cambridge Digital Library ( and a variety of Digital Humanities projects. She has a PhD in the landscape archaeology and material culture of Anglo-Saxon England, which focussed on spatial analysis with GIS and the methodology of metal detecting. During the Methods Fellowship, Mary will be teaching two introductory workshops to Text-Mining with Python.



Dr Oliver Dunn


Oliver's research background is in the economic, social and cultural history of England 1500–1900. He has degrees from Bristol and Cambridge Universities and a PhD in European History and Civilisation from the European University Institute in Italy. He has worked professionally on and off since 2006 with the Cambridge Group for the History of Population and Social Structure, Cambridge, mentored by Leigh Shaw-Taylor. In this role Oliver has aided historical research into very long-term demographic and economic trends in England and Wales using quantitative methods and countless archival sources.



Leonardo Impett (Visiting Fellow)​

Leo's research ambition is broadly to attempt to do for visual art what the Stanford Literary Lab has done for literary fiction: an approach which combines large-scale computational analysis with conventional criticism and theory. Doing computation on images (looking for objects, gestures, iconographies) is inherently more difficult than text (recognising word frequencies, classes, cases), but computer vision gives us the tools to close that gap. He is therefore active in the computer vision community, including through the VISART (at the European Conference on Computer Vision) and Ways of Machine Seeing (at Cambridge). In this way, Digital Art History can go beyond replicating other methods from the digital humanities (network analysis, mapping, digital editions), but develop its own computational methodologies specific to the image.

Computer vision necessarily embodies a theory of vision (primarily a neuroscientific one): conversely, important discoveries in the theory of vision have come from computer vision algorithms. Leo's current project, Early Modern Computer Vision, therefore attempts to prototype a computer vision system (that is to say, a set of formal instructions for machines to read images) which is based on Italian theories of optics, vision and visual art of the 16th century (particularly of Gian Paolo Lomazzo) as an experimental apparatus to investigate those theories.



Dr Hugo Leal

Hugo is a Research Associate at the Centre for Research in the Arts, Social Sciences and Humanities (CRASSH), University of Cambridge. He was a Postdoctoral Fellow in the internet branch of the project "Conspiracy & Democracy" and is currently a Methods Fellow at Cambridge Digital Humanities (CDH).

Hugo combines research and teaching activities on misinformation, collective action and digital methods. His current research focuses on three topics: a cross-comparative analysis of conspiracy beliefs in Europe and the United States; the strategic use of misinformation by political actors; and nativist mobilisation driven by beliefs in the “Islamisation of Europe”. Also in the pipeline is the examination of “alternative knowledge” networks and their effects in the public perception of scientific and public health debates. His work cuts across disciplines, from sociology to political science, and combines qualitative and quantitative methods, with an emphasis on digital methods and social network analysis.




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