HOME ABOUT NEWS COLLABORATION PUBLICATIONS CONTACT MODE@TWITTER







Machine-learning Optimized Design of Experiments

ABOUT

MODE (for Machine-learning Optimized Design of Experiments) is a nascent collaboration of physicists and computer scientists who target the use of differentiable programming 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 a modular, customizable, and scalable, fully differentiable pipeline 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 has been submitted in a concise form as an expression of interest to the JENAA group.
News

NEWS


Collaboration

COLLABORATION


The MODE Collaboration includes:

At University of Padova Dr. Tommaso Dorigo, Dr. Pablo De Castro Manzano, Dr. Lukas Layer, Prof. Roberto Rossin, Dr. Giles Strong, Dr. Mia Tosi, Dr. Hevjin Yarar
At Universite' Catholique de Louvain Dr. Andrea Giammanco, Prof. Christophe Delaere, Dr. Pietro Vischia
At Universite' Clermont Auvergne, Prof. Julien Donini and Dr. Djamel Boumediene
At the Higher School of Economics of Moscow, Prof. Andrey Ustyuzhanin, Dr. Denis Derkach and Dr. Fedor Ratnikov

In addition, the following experts in computer science and physics applications of Machine Learning are MODE collaborators:
At CERN Dr. Jan Kieseler
At University of Oxford Dr. Atilim Gunes Baydin
At New York University Prof. Kyle Cranmer
At Universite' de Liege Prof. Gilles Louppe
Publications

PUBLICATIONS


Below is a concise list of relevant publications to the research interests of the MODE collaboration:

Contacts

CONTACTS

Send e-mail Dr. Tommaso Dorigo
First Researcher, INFN-Padova
Email: dorigo (at) pd (dot) infn (dot) it
Phone:


Office tel.: +39 0499677230
Mobile tel.: +39 3666995594

Snail mail:
Dipartimento di Fisica e Astronomia "G.Galilei"
via Francesco Marzolo 8, 35131 Padova
ITALY