Speaker
Description
I am co-author of the DYTURBO event generator, predicting the differential cross-sections of vector boson production at the LHC. In order to improve the speed during the phase-space integration process, I would like to develop/include DNN-based phase-space sample algorithms.
Furthermore I am working on DNN based unfolding techniques and would be interested to extend the unfolding aspect to folding aspects, i.e. the full detector simulation.
My current most burning research question, I like to find partners for, is:
Speed improvement of MC Event Generators and Detector Simulations using Deep Neural Networks
Please describe areas in which you would like to improve your knowledge / skills.
Phase-Space Sampling using DNNs
Please describe your expertise/areas in which you would like to contribute / advise.
Improvements of Detector Simulations, Physic Object Reconstructions using Deep Neural Networks
In ErUM-Data, what kind of data are you dealing with?
Data from ATLAS
Please describe areas in which you can contribute to “data handling” teaching.
Regular Classes of Artificial Intelligence as well as Statistics for Computer Science Students in Mainz / Marburg
What is your field and role?
Experimental Particle Physics (Uni Mainz) and Computer Science (Uni Marburg)
What is your expertise in computing and / or software development?
Master in Computer Science with Focus on Artificial Intelligence, Guest-Professor at the Institute of Computer Science of the Uni. Marburg for "Simulations" from September 2021 onwards
| Your ErUM - Committee is | KET - Komitee für Elementarteilchenphysik |
|---|---|
| Do you consent to the data usage and public abstract data posting in the ErUM-Data Community Information Exchange? | Yes |
