1st Conference on Machine Learning for Gravitational Waves, Geophysics, Robotics, Control System and CA17137 MC2 meeting

14 Jan 2019, 08:30 → 16 Jan 2019, 18:00 Europe/Rome

EGO Auditorium

Elena Cuoco

Action description

The breakthrough discovery of gravitational waves on September 14, 2015 was made possible through synergy of techniques drawing from expertise in physics, mathematics, information science and computing.  At present, there is a rapidly growing interest in Machine Learning (ML), Deep Learning (DL), classification problems, data mining and visualization and, in general, in the development of new techniques and algorithms for efficiently handling the complex and massive data sets found in what has been coined "Big Data", across a broad range of disciplines, ranging from Social Sciences to Natural Sciences. The rapid increase in computing power at our disposal and the development of innovative techniques for the rapid analysis of data will be vital to the exciting new field of Gravitational Wave (GW) Astronomy, on specific topics such as control and feedback systems for next-generation detectors, noise removal, data analysis and data-conditioning tools.The discovery of GW signals from colliding binary black holes (BBH) and the likely existence of a newly observable population of massive, stellar-origin black holes, has made the analysis of low-frequency GW data a crucial mission of GW science. The low-frequency performance of Earth-based GW detectors is largely influenced by the capability of handling ambient seismic noise suppression. This Cost Action aims at creating a broad network of scientists from four different areas of expertise, namely GW physics, Geophysics, Computing Science and Robotics, with a common goal of tackling challenges in data analysis and noise characterization for GW detectors.

Poster1stCA17137conference.pdf

Monday 14 January

Registration

Welcome of the EGO Director and Chair's Introduction about CA17137

Conveners: Elena Cuoco, Stavros Katsanevas

1stMeeting_EC.pdf

Introduction to Gravitational Waves

1 "Imbedding large reasearch infrastructures in the earth environment, the case for Virgo".

Speaker: Prof. Katsanevas Stavros

COST_pisa_14jan2019.pptx

2 The future of Gravitational Waves detectors: toward Einstein Telescope

Speaker: Michele Punturo (INFN)

ET-COST-Jan2019-Optimised.pptx

11:00 coffee break

Introduction to Gravitational Waves

3 Coupling between seismic noise and diffuse light in GW detector

Speaker: Dr Antonino Chiummo (European Gravitational Observatory)

Coupling between seismic noise and diffuse light in GW detector - talk @COST meeting

4 Hunting environmental noise in Virgo

Speaker: Irene Fiori (European Gravitational Observatory)

Fiori_noiseHunting.pdf

Fiori_noiseHunting.pptx

5 Applications of Machine Learning in seismology

Speaker: Dr Alberto Michelini (alberto.michelini@ingv.it)

presentation_seismology.pdf

13:00 Lunch

ML for Advanced Control techniques

6 WG3 introduction

Speaker: Jan Harms

Cascina_JH.pdf

7 Angular controls in Virgo

Speaker: Julia casanueva diaz

Alignment_Virgo.pdf

8 Feed-forward noise cancellation in Virgo

Speaker: Dr Diego Bersanetti (INFN Genova)

ML_Workshop_FF.pdf

9 ML for noise cancellation in systems with non-linear coupling

Speaker: Alberto Iess (University of Rome Tor Vergata)

Presentation_CA17137_jan_2019_pdf.pdf

16:00 coffee break

ML for Advanced Control techniques

10 ML and genetic algorithms for noise cancellation

Speaker: Alessio Cirone

Cirone_14Gen2019_COSTactionVirgo.pdf

11 Non-stationary noise cancellation with causal, stable parametric filters

Speaker: Dr Gabriele Vajente

COST_WG3_2019_01_14(1).pdf

Tuesday 15 January

ML for low-frequency seismic measurement

12 WG2 introduction

Speaker: Alessandro Bertolini

wg2_session_intro.pdf

wg2_session_intro.pptx

13 Newtonian Noise subtraction test array at Virgo

Speaker: Tomasz Bulik

TB-talk.pdf

14 Robots for GW detectors and infrastructure monitoring and operation: Can Networks of Autonomous Robotics Vehicles help the characterization of Newtonian, Acoustic and Other Source Noise in GW detection?

Speaker: Prof. Fabio Bonsignorio (Scuola Superiore Sant'Anna)

NetRobNNEgoVirgoApril16V1.8.3.6.pptxPdf.pdf

15 Machine Learning for seismic events

Speaker: Ms Jozinović Dario (INGV)

ConvNetQuake_INGV.pdf

16 Generalized maximum entropy inference for seismic models

Speaker: Dr Velimir Ilic

11:15 coffee break

Virgo Visit

13:00 lunch

ML for low-frequency seismic measurement

17 GW detector sites characterization with seismic arrays

Speaker: Soumen Koley (Nikhef)

PassiveSeismic.pptx

18 Short Term Scientific Mission Call

Speaker: Apolinario Liliana

Apolinario

ML for GW astronomy

19 WG1 introduction

Speaker: Michal Bejger

WG1 Introduction.pdf

20 Total-variation and dictionary learning methods for gravitational-wave data analysis

Speaker: Jose Antonio Font-Roda

talk-1st-COST.pdf

16:00 coffee break

ML for GW astronomy

21 Gravitational Wave Open Science Center: how to access LIGO/Virgo open data

Speaker: Dr Agata Trovato

2019_01_15_Trovato_novideo.pdf

22 Image-based transient signal classification with deep learning

Speaker: Massimiliano Razzano

2019_0114_g2net_ml_razzano_v2.pdf

23 Deep Learning Methods for Predictive Tasks with Large Scale Sensor Data

Speaker: Dr Roberto Corizzo

talk-roberto-corizzo.pdf

Wednesday 16 January

Closed Sessions: WG1, WG2, WG3 meetings

11:00 coffee break

Closed Session: MC Meeting

13:00 Lunch

Closed Session: MC Meeting