The Machine-learning Optimized Design of Experiments (MODE) is a collaboration of physicists and computer scientists who target the use of differentiable programming in design optimization of experiments in various fields of applied sciences and engineering.

The MODE collaboration involves in design optimization of detectors for particle physics applications, extending from fundamental research at accelerators, in space, and in nuclear physics and neutrino facilities, to industrial applications employing the technology of radiation detection. We aim to develop modular, customizable, and scalable, fully differentiable pipelines for the end-to-end optimization of articulated objective functions that model in full the true goals of experimental particle physics endeavours, to ensure optimal detector performance, analysis potential, and cost-effectiveness.
The main goal of our activities is to develop an architecture that can be adapted to the above use cases but will also be customizable to any other experimental endeavour employing particle detection at its core. We welcome suggestions, as well as interest in joining our effort, by researchers focusing on use cases for which this technology can be of benefit.
The above program is supported as an expression of interest by the Jenna Group .
If you are interested in information about MODE (including, but not limited to, the announcement of our yearly workshop and the opening of MODE-related PhD/postdoc positions), or if you want to post such advertisement yourself, you can join our mode-info mailing list !
Get in touch with MODE Collaboration
Scientific Coordinator
Prof. Pietro Vischia
Email: pietro (dot) vischia (at) cern (dot) ch
Office tel.: +34 985 106 252
Mobile tel.: +34 (six)(six)(six) (nine)(eight)(six) (six)(one)(six)
Snail mail:
Departamento de Física, edificio de Geología,
C/ Jesús Arías Velasco s/n,
33005 Oviedo, Principado de Asturias, España.
Steering Board
The whole Steering Board can be reached by writing to: mode-collaboration-sb(at)cern(dot)ch
The Steering Board of the MODE Collaboration includes:
Previous Steering Boards:
2025: Pietro Vischia (UNIOVI, coordinator), Tommaso Dorigo (INFN-PD), Nicolas Gauger (RPTU), Andrea Giammanco (UCLouvain), Christian Glaser (UU), Lisa Kusch (TU/e), Fedor Ratnikov (HSE)
2020-2024: Tommaso Dorigo (INFN-PD, coordinator), Julien Donini (UCA), Andrea Giammanco (UCLouvain), Fedor Ratnikov (HSE), Pietro Vischia (UniOvi)