Name: Where the Earth Meets the Sky
Start: 2021-05-27T08:00:00+02:00
End: 2021-05-28T18:05:00+02:00
Location: online

Where the Earth Meets the Sky

from Thursday 27 May 2021 (08:00) to Friday 28 May 2021 (18:05)

Monday 24 May 2021
Tuesday 25 May 2021
Wednesday 26 May 2021
Thursday 27 May 2021

09:00 Webinar is now open for connections
Webinar is now open for connections
09:00 - 09:20

09:20 Welcome and introduction
Welcome and introduction
09:20 - 09:30
Room: Zoom Webinar A few words from the organizers to introduce the first day of the workshop.
09:30 first half
first half
09:30 - 10:50
Contributions

09:30 When the brain meets the sky: Compressed Sensing for Magnetic Resonance Imaging & Radio-Astronomy - Jean-Luc STARK (CEA Saclay, CosmoStat laboratory) Philippe CIUCIU (CEA Saclay, Neurospin)

10:10 Time Series Classification: From Astronomical Transients to Human Heart Sounds - Motahare TORKI (Shahid Beheshti University)

10:30 Deep learning framework for clinical diagnosis - a healthcare system - Sandeep Singh SENGAR (University of Copenhagen, Denmark)
10:50 Break
Break
10:50 - 11:15
11:15 second half
second half
11:15 - 12:30
Contributions

11:15 Supervised classification of variable stars from the NASA TESS survey with features originating from the biomedical domain - Jeroen AUDENAERT (KU Leuven, Institute of Astronomy)

11:35 Towards an interpretable and transferable acoustic emotion recognition for the detection of mental disorders - Sneha DAS (Technical University of Denmark)

11:55 Hand-On Image Processing with PySAP - Samuel FARRENS (CosmoStat, CEA Paris-Saclay)
12:30 Lunch break
Lunch break
12:30 - 13:30
13:30 four posters
four posters
13:30 - 14:00
Contributions

13:30 The AstroPath Image Acquisition and Segmentation Workflow - Benjamin GREEN (Johns Hopkins University)

13:35 Automated morphological decomposition of galaxies in large imaging surveys - Sarah CASURA (Universität Hamburg, Germany)

13:40 Building Seamless Whole Slide Multiplex Images in the AstroPath Project - Jeffrey ROSKES (Johns Hopkins University)

13:45 ODUSSEAS: a machine learning tool to derive effective temperature and metallicity for M dwarf stars - Alexandros ANTONIADIS KARNAVAS (Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto)
14:00 first half
first half
14:00 - 15:20
Contributions

14:00 The role of domain knowledge experts in the era of big data - Emille ISHIDA (CNRS/Laboratoire de Physique de Clermont)

14:40 Training an interpretable ML algorithm with only a dab of real data: An extragalactic perspective - Aritra GHOSH

15:00 PyAutoFit: A Classy Probabilistic Programming Language For Cosmology and Cancer - James NIGHTINGALE (Durham University)
15:20 Break
Break
15:20 - 15:45
15:45 second half
second half
15:45 - 17:05
Contributions

15:45 Modelling spatial phenomena: a brief tour of the current state of the art - Samir BHATT (University of Copenhagen, Imperial College London)

16:25 AstroPath: Astronomy Meets Pathology to Characterize the Tumor MicroEnvironment - Alexander SZALAY (Johns Hopkins University)

16:45 Correcting for Systematics in Multiplex Cancer Imaging in the AstroPath Project - Margaret EMINIZER (The Johns Hopkins University)
17:05 Wrap-up and see you next morning
Wrap-up and see you next morning
17:05 - 17:20
Room: Zoom Webinar
Friday 28 May 2021

09:00 Webinar is now open for connections
Webinar is now open for connections
09:00 - 09:20

09:20 Welcome back
Welcome back
09:20 - 09:30
Room: Zoom Webinar A few words from the organizers to introduce the 2nd day of workshop.
09:30 first half
first half
09:30 - 10:50
Contributions

09:30 Longitudinal Disease Trajectories at Population Scale - Søren BRUNAK

10:10 Fast complex dynamics emulators using deep generative models - Doogesh KODI RAMANAH (DARK, Niels Bohr Institute, University of Copenhagen)

10:30 CycleGANs can bridge to understanding/closing the reality gap for CMB simulations - Alireza VAFAEI SADR (university of Geneva)
10:50 Break
Break
10:50 - 11:15
11:15 second half
second half
11:15 - 12:30
Contributions

11:15 How is deep learning useful to understand the physics of galaxies? - Marc HUERTAS-COMPANY

11:55 What to do with curved distributions in MCMC - Filippo PAGANI (University of Cambridge)
12:30 Lunch break
Lunch break
12:30 - 13:30
13:30 seven posters
seven posters
13:30 - 14:20
Contributions

13:30 Anomaly Detection using Dimensionality reduction - an Active learning approach. - Emmanuel SEKYI (African Institute for Mathematical Sciences, Cape Town)

13:35 A Method to Distinguish Quiescent and Dusty Star-forming Galaxies with t-SNE - John WEAVER (Cosmic Dawn Center, NBI)

13:40 Deep Multi-Task Learning for Series Classification by Pulse Sequence Type and Orientation - Noah KASMANOFF (New York University)

13:45 Novel Application in Machine Learning: Predicting the Issuance of COVID-19 Stay-at-Home Orders in Africa - Carter RHEA (L'Université de Montréal)

13:50 A new vocabulary for textures and its astronomical applications - Sihao CHENG (Johns Hopkins University)

13:55 Cross-Registration of Whole Slide Images from Different Modalities in AstroPath - Joshua DOYLE (Johns Hopkins University)

14:00 CellView: an Interactive Image Viewer for Multiplex Cancer Images in the AstroPath Project - Dmitry MEDVEDEV (Johns Hopkins University)
14:20 first half
first half
14:20 - 15:20
Contributions

14:20 Searching for needles in the cosmic haystack - Ashley VILLAR (Columbia University)

14:40 Domain Adaptation for Cross-Domain Studies in Astronomy: Merging Galaxies Identification - Aleksandra CIPRIJANOVIC (Fermi National Accelerator Laboratory, USA)

15:00 Bayesian Model Comparison applied to COVID 19 - Pablo LEMOS (University of Sussex)
15:20 Break
Break
15:20 - 15:45
15:45 second half
second half
15:45 - 16:05
Contributions

15:45 Chaotic_Neural: Improving Literature Surveys in Astronomy with Machine Learning - Kartheik IYER (Dunlap Institute for Astronomy and Astrophysics, University of Toronto)
16:05

16:05 - 16:50
Room: Zoom meeting room

16:50 Final remarks and goodbye
Final remarks and goodbye
16:50 - 17:00

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