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Keynote Lectures

More than Meets the Eye: Towards an Artificial Intelligence Observatory
Matias Carrasco Kind, University Illinois Urbana Champaign, United States

Keynote Lecture
Barbara Caputo, Politecnico di Torino, Italy

 

More than Meets the Eye: Towards an Artificial Intelligence Observatory

Matias Carrasco Kind
University Illinois Urbana Champaign
United States
 

Brief Bio
Matias Carrasco Kind is currently a Senior Research Scientist at the National Center for Supercomputing Applications (NCSA), Assistant Research Professor in Astronomy and the Associate Director of the Data Science Research Services at the Gies College of Business at the University of Illinois at Urbana-Champaign in the U.S.

He is interested in challenging problems involving data intensive science, machine, and deep learning, data mining, data analysis and visualization, image processing, AI generative models, scientific platforms and cyberinfrastructure, data management, software engineering, and scientific cloud computing, among others. Most of his research has been focused on Astrophysics but given the multidisciplinary nature of his work, and the common needs and tools across multiple fields regarding data, he has also applied these techniques to earth sciences, bio-imaging, veterinary, agricultural economics, finance research, and accounting.

Matias obtained his PhD in Astronomy with a Computational Science and Engineering option at the University of Illinois which focused on machine learning techniques applied to astronomy at large scales. 


Abstract
What if, by leveraging the rapid development of AI, cyber-infrastructure, and astronomical surveys we can create an extremely intelligent machine with infinite knowledge that after being feed with all of the available survey data from all the sources and wavelengths is able to recreate every observation for any object in any wavelength? What if we can feed that entity with an optical image and ask for a radio counterpart? Or ask it to generate infrared data from a given set of properties? Will, that machine been able to make inferences from new observations, assuming its infinite memory?

Even though this might sound too much science-fiction, 10 to 15 years from now might be an incubating project which needs to start today. In this talk, I'll discuss what efforts have been made in this direction, what deep learning advances might help us think in that future, how data from multiple surveys and telescopes can be combined in taking the first steps, and what have we done to make this happen.

Thanks to the advancement of computing, AI, and gateways techniques, the possibilities are countless, and it is now that we need to think about these issues in order to be prepared and to understand how information can be extracted intelligently in favor of scientific discoveries.



 

 

Keynote Lecture

Barbara Caputo
Politecnico di Torino
Italy
 

Brief Bio
Available soon.


Abstract
Available soon.



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