Tristan Dot, St John's

Degree: PhD
Course: English
Supervisor: Dr Leo Impett
Dissertation Title:

19th century textile patterns in Great Britain – a computational approach


Biographical Information

Tristan is a PhD candidate in digital art history at the University of Cambridge. He is working on 19th century textile patterns in Great Britain, their diversification and diffusion through the Jacquard loom and grammars of ornaments. He is also interested in the epistemology, and long historiography of digital art history – in particular, its links with formalism and structuralism.

Before starting his PhD, Tristan studied art history, mathematics and computer science. He received a M.Sc. degree in applied mathematics from ENS Paris-Saclay, a B.A. & M.A. (1) in art history from Pantheon-Sorbonne University, and worked as a research engineer in digital humanities at the Paris Observatory.

Research Interests

19th century textiles; the Jacquard loom; grammars of ornaments; material culture; global art history; history of weaving technologies; computer vision & image processing; formalism; structuralism; digital humanities.

Selected Publications

Talks and invited lectures:

• "Following the grid: on some prefigurations of digital art history", Styles Revisited: From Iconology to Digital Image Studies, University of Geneva, Seminar (May 2023).

• "Discrete image, grid, matrix: possibilities of encoding/decoding (weaving/unweaving)", From Hype to Reality: Artificial Intelligence in the Study of Art and Culture, University of Zurich, Symposium (April 2023).

• "Computer vision and artwork analysis", Des chiffres et des arts, École Normale Supérieure (ENS), Lecture (December 2022).

• "Automatic table transcription in manuscripts", Digital Humanities Meet Artificial Intelligences, École Normale Supérieure (ENS), Seminar (November 2021).

Publications in computer science:

• "Non-Linear Template-Based Approach for the Study of Locomotion", Tristan Dot, François Quijoux, Laurent Oudre, Aliénor Vienne-Jumeau, Albane Moreau, Pierre-Paul Vidal, David Ricard, Sensors 2020, 20, 1939.

• "Deep learning from phylogenies to understand the dynamics of epidemics.", Jakub Voznica, Anna Zhukova, Tristan Dot, Kary Ocaña, Frédéric Lemoine, et al.., Epidemics - 7th International Conference on Infectious Disease Dynamics, Dec 2019, Charleston, United States.