Gabriele Morra
2019-11-19 22:33:43
Dear Colleagues
We wish to bring to your attention to the upcoming
scientific workshop titled "SCIWS3: Applications of Big Data and
High-Performance Computing in Earth Sciences" that will happen on Sunday
December 8, from 8am to 4pm at GB East, Grand Hyatt.
This is a follow up of the successful workshop on Machine Learning and
Jupyter of the past year, which focused on introducing Data Science from a
pedagogical stance to beginners and on implementations for seismology. In
2019 our intent is to dwell more on applications use of Data Analytics to a
broader arena by including more fields such as geochemistry, structural
geology, mineral physics, volcanology, geodynamics, planetary sciences. An
important part of the workshop will be devoted to technical talks that will
cover high-performance computing algorithms for Big Data processing and for
Machine Learning, with a major focus on Neural Network.
Some of the confirmed invited speakers and the title of their presentations
will be:
*Ebru Bozdag (Colorado School of Mines)*: Global full-waveform inversion:
Combining big data with high-performance computing to image the solid Earth
*Natasha Flyer (National Center for Atmospheric Research)*: Developing
Convolutional Neural Networks for Predicting the Strength of Geomagnetic
Storms Caused by Interplanetary Coronal Mass Ejections
*Peter Gerstoft (Scripps Institute, San Diego) *: Generative Modeling and
Variational Auto-Encoders
*Lindsey Heagy (University of British Columbia)*: Jupyter meets the Earth:
from geophysical inversions to open, collaborative geoscience
*Owen Kaluza (Monash University)*: The IPython/Jupyter Scientific
Visualisation Landscape
*Kyle Mandli (Columbia University)*: Surrogate and reduced order models
applied to uncertainty quantification of storm surge risk assessment and
sensitivity
*Ludovic Raess (Stanford University)*: Revamping HPC in Earth science using
Julia: a multi-GPU PDE solver
*Hosein Shahnas (University of Toronto)*: Machine Learning and Deep
Learning in Geodynamics and Earth Sciences
*Natalia Sidorovskaia (University of Louisiana at Lafayette)*: Big data
paradigm in ocean acoustic ecology
*Frederik Simons (Princeton University)*: Spectral-Density Estimation of
Gaussian Processes for Multivariable Multidimensional Problems
*Manoochehr Shirzaei (Arizona State University)*: Wavelets in Spaceborne
Remote Sensing and Applications to Groundwater Hydrogeodesy
*Velimir Vesselinov (Los Alamos National Labs)*: Unsupervised and
Physics-Informed Machine Learning of Big and Noisy Data
*Lin, Youzuo (Los Alamos National Labs)*: Computational Methods for
Large-scale Inverse Problems: Physics-driven VS Data-driven or Combined?
The workshop is open to AGU Fall Meeting attendees and carries an
additional registration fee, $150 Regular and $75 for Students. Students
are welcomed and time for open discussion will be allotted during
the workshop.
How to register:
https://agu.confex.com/agu/fm19/meetingapp.cgi/Session/76617
For more information, please contact us at
Gabriele Morra (gabrielemorra<at>gmail.com) or
Dave Yuen (daveyuen<at>gmail.com)
Best regards
Gabriele Morra and Dave Yuen
Gabriele Morra
http://scholar.google.com/citations?sortby=pubdate&hl=en&user=DDuTppAAAAAJ&view_op=list_works
Associate Professor https://physics.louisiana.edu/about-us/faculty-staff
Department of Physics http://physics.louisiana.edu and School of
Geosciences http://geos.louisiana.edu
University of Louisiana at Lafayette http://www.louisiana.edu
Forthcoming AGU workshop: Applications of Big Data and HPC in Earth Sciences
https://agu.confex.com/agu/fm19/meetingapp.cgi/Session/76617
Co-Editor in Chief of *Artificial Intelligence in the Geosciences
http://www.keaipublishing.com/en/journals/artificial-intelligence-in-geosciences/*
We wish to bring to your attention to the upcoming
scientific workshop titled "SCIWS3: Applications of Big Data and
High-Performance Computing in Earth Sciences" that will happen on Sunday
December 8, from 8am to 4pm at GB East, Grand Hyatt.
This is a follow up of the successful workshop on Machine Learning and
Jupyter of the past year, which focused on introducing Data Science from a
pedagogical stance to beginners and on implementations for seismology. In
2019 our intent is to dwell more on applications use of Data Analytics to a
broader arena by including more fields such as geochemistry, structural
geology, mineral physics, volcanology, geodynamics, planetary sciences. An
important part of the workshop will be devoted to technical talks that will
cover high-performance computing algorithms for Big Data processing and for
Machine Learning, with a major focus on Neural Network.
Some of the confirmed invited speakers and the title of their presentations
will be:
*Ebru Bozdag (Colorado School of Mines)*: Global full-waveform inversion:
Combining big data with high-performance computing to image the solid Earth
*Natasha Flyer (National Center for Atmospheric Research)*: Developing
Convolutional Neural Networks for Predicting the Strength of Geomagnetic
Storms Caused by Interplanetary Coronal Mass Ejections
*Peter Gerstoft (Scripps Institute, San Diego) *: Generative Modeling and
Variational Auto-Encoders
*Lindsey Heagy (University of British Columbia)*: Jupyter meets the Earth:
from geophysical inversions to open, collaborative geoscience
*Owen Kaluza (Monash University)*: The IPython/Jupyter Scientific
Visualisation Landscape
*Kyle Mandli (Columbia University)*: Surrogate and reduced order models
applied to uncertainty quantification of storm surge risk assessment and
sensitivity
*Ludovic Raess (Stanford University)*: Revamping HPC in Earth science using
Julia: a multi-GPU PDE solver
*Hosein Shahnas (University of Toronto)*: Machine Learning and Deep
Learning in Geodynamics and Earth Sciences
*Natalia Sidorovskaia (University of Louisiana at Lafayette)*: Big data
paradigm in ocean acoustic ecology
*Frederik Simons (Princeton University)*: Spectral-Density Estimation of
Gaussian Processes for Multivariable Multidimensional Problems
*Manoochehr Shirzaei (Arizona State University)*: Wavelets in Spaceborne
Remote Sensing and Applications to Groundwater Hydrogeodesy
*Velimir Vesselinov (Los Alamos National Labs)*: Unsupervised and
Physics-Informed Machine Learning of Big and Noisy Data
*Lin, Youzuo (Los Alamos National Labs)*: Computational Methods for
Large-scale Inverse Problems: Physics-driven VS Data-driven or Combined?
The workshop is open to AGU Fall Meeting attendees and carries an
additional registration fee, $150 Regular and $75 for Students. Students
are welcomed and time for open discussion will be allotted during
the workshop.
How to register:
https://agu.confex.com/agu/fm19/meetingapp.cgi/Session/76617
For more information, please contact us at
Gabriele Morra (gabrielemorra<at>gmail.com) or
Dave Yuen (daveyuen<at>gmail.com)
Best regards
Gabriele Morra and Dave Yuen
Gabriele Morra
http://scholar.google.com/citations?sortby=pubdate&hl=en&user=DDuTppAAAAAJ&view_op=list_works
Associate Professor https://physics.louisiana.edu/about-us/faculty-staff
Department of Physics http://physics.louisiana.edu and School of
Geosciences http://geos.louisiana.edu
University of Louisiana at Lafayette http://www.louisiana.edu
Forthcoming AGU workshop: Applications of Big Data and HPC in Earth Sciences
https://agu.confex.com/agu/fm19/meetingapp.cgi/Session/76617
Co-Editor in Chief of *Artificial Intelligence in the Geosciences
http://www.keaipublishing.com/en/journals/artificial-intelligence-in-geosciences/*
