PoS - Proceedings of Science

Artificial Intelligence for Science, Industry and Society

21-25 October, 2019
Universidad Nacional Autónoma de México, Mexico City, México
published January 28, 2021
Entries on ADS

The recent progress in Artificial Intelligence and Machine Learning has provided new ways to process large data sets. The new techniques are particularly powerful when dealing with unstructured data or data with complex, non-linear relationships, which are hard to model and analyse with traditional, statistical tools. This has triggered a flurry of activities both in industry and science, developing methods to tackle problems which used to be impossible or extremely hard to deal with.


Due to this situation, we are proposing to organise a meeting where the following key elements would be covered:

The meeting is oriented towards scientists and educators as well as industry and policy makers in R&D.


Editorial Board


Boris Escalante , CViCom-UNAM

Federico Carminati , CERN

Guy Paic , ICN-UNAM

Lukas Nellen , ICN-UNAM

Rafael Mayo , CIEMAT

Steven Schramm , University of Geneva

Zeljko Ivezic , University of Washington

Editorial Board

conference main image
Day 1
Day 2
Day 4
Day 5
Editor’s Note for the Proceedings of the Artificial Intelligence for Science, Industry and Society – AISIS2019
PoS(AISIS2019)048 pdf G.G. Barnaföldi, L. Nellen and G. Paic
Day 1
Galaxy Morphology classification using CNN
PoS(AISIS2019)006 pdf J.A. Vázquez-Mata, H.M. Hernandez-Toledo and L.C. Mascherpa
Generative Model Study for 1+1d-Complex Scalar Field Theory
PoS(AISIS2019)007 pdf attachments K. Zhou, G. Endrodi, L.G. Pang and H. Stoecker
Studying the parton content of the proton with deep learning models
PoS(AISIS2019)008 pdf J.M. Cruz Martinez, S. Carrazza and R. Stegeman
Online Estimation of Particle Track Parameters based on Neural Networks for the Belle II Trigger System
PoS(AISIS2019)010 pdf S. Baehr, K.L. Unger, J. Becker, F. Meggendorfer, S. Skambraks and C. Kiesling
Generative Adversarial Networks for Fast Simulation: distributed training and generalisation
PoS(AISIS2019)012 pdf F. Carminati, S. Vallecorsa, G. Khattak, V. Codreanu, D. Podareanu, M. Cai, V. Saletore and H. Pabst
Portraying Double Higgs at the Large Hadron Collider
PoS(AISIS2019)013 pdf M. Kim, J. Kim, K.C. Kong, K.T. Matchev and M. Park
Day 2
Trustworthy AI. The AI4EU approach
PoS(AISIS2019)014 pdf U. Cortés, A. Cortés and C. Barrué
Regulating Emerging Technologies: Opportunities and Challenges for Latin America
PoS(AISIS2019)015 pdf M. Stankovic and N. Neftenov
Deep learning for cosmology
PoS(AISIS2019)021 pdf C. Escamilla-Rivera
A machine learning approach for the feature extraction of pulmonary nodules
PoS(AISIS2019)024 pdf attachments C.I. Loeza Mejía, R.R. Biswal and G. Fernandez Lambert
Skin Lesion Detection in Dermatological Images using Deep Learning
PoS(AISIS2019)025 pdf J.C. Moreno-Tagle, J. Olveres and B. Escalante-Ramírez
QUA³CK - A Machine Learning Development Process
PoS(AISIS2019)026 pdf S.C. Stock, J. Becker, D. Grimm, T. Hotfilter, G. Molinar, M. Stang and W. Stork
Regularization methods vs large training sets
PoS(AISIS2019)028 pdf J.J. Vega, H. Carrillo-Calvet and J.L. Jiménez-Andrade
Day 4
Large-Scale Scientific endeavours: the production and dissemination of advance computer sciences knowledge
PoS(AISIS2019)040 pdf A. Sanchez Pineda
Machine Learning-Based System for the Availability and Reliability Assessment and Management of Critical Infrastructures (CASO)
PoS(AISIS2019)041 pdf L. Serio
Day 5
Robotics, AI and Machine Vision
PoS(AISIS2019)043 pdf J. Savage, A. Nakayama and C. Sarmiento
Machine learning in accelerator physics: applications at the CERN Large Hadron Collider
PoS(AISIS2019)044 pdf F. Van Der Veken, G. Azzopardi, F. Blanc, L. Coyle, E. Fol, M. Giovannozzi, T. Pieloni, S. Redaelli, B.M. Salvachua Ferrando, M. Schenk, R. Tomas Garcia and G. Valentino
Policies for Artificial Intelligence in Science and Innovation
PoS(AISIS2019)045 pdf A. Paic
Quantum Computing Future-Proofing What Lies Beyond SuperComputing
PoS(AISIS2019)047 pdf S.L. Hamilton