2020 Accelerated Artificial Intelligence for Big-Data Experiments Conference


Note: All times are U.S. Central

Events will be webcast via Zoom

Monday, October 19

8:45 am
Eliu Huerta
9:00 am
Big Data and Computational Grand Challenges in Astronomy, Multi-Messenger Astrophysics and High Energy Physics
Presentations by:


Chair: Janice Lee, California Institute of Technology/IPAC

Ryan Hausen
Dimitrios Tanoglidis
Christine Ye
John Wu
Catarina Alves

15-minute Q&A session

Multi-Messenger Astrophysics

Chair: Erik Katsavounidis, Massachusetts Institute of Technology

Michael Coughlin
Ashley Villar
Kaze W. K. Wong
Agata Trovato
Leïla Haegel
Gautham Narayan

15-minute Q&A session

High Energy Physics

Chair: Philip Harris, Massachusetts Institute of Technology

David Rousseau
Gage DeZoort
Maximilian Swiatlowski
Mike Wang
Benjamin Nachman

15-minute Q&A session
11:15 am
11:30 am
Innovative Software and Hardware Architectures for AI
Chair: Volodymyr Kindratenko

Tom Gibbs, NVIDIA

Nick Fraser, Xilinx

Sergiu Sanielevici, Neocortex
12:30 pm
Lunch/Poster Session
Presentations by:


Chair: Andreas Faisst, California Institute of Technology/IPAC

Dmitry Duev
Xiaolong Li
Attila Bódi

Multi-Messenger Astrophysics

Chair: Andreas Faisst, California Institute of Technology/IPAC

Stephen Green
Adriano Baldeschi
Jessica Krick

High Energy Physics

Chair: Dylan Rankin, Massachusetts Institute of Technology

Florian Rehm
Rui Zhang
Charanjit Kaur Khosa
1:30 pm
AI Innovation for Astronomy, Multi-Messenger Astrophysics and High Energy Physics
Presentations by:


Chair: Brad Whitmore, Space Telescope Science Institute

Sankalp Gilda
Matthew Graham
Peter Yoachim

10-minute Q&A session

Multi-Messenger Astrophysics

Chair: Raffaella Margutti, Northwestern University

Asad Khan
Monika Soraisam
Tri Nguyen

10-minute Q&A session

High Energy Physics

Chair: Javier Duarte, University of California San Diego

Chris Tunnell
Marina Krstic Marinkovic
Mia Liu

10-minute Q&A session
2:45 pm
3:00 pm –
5:30 pm
Vision for the Future
Chair: Eliu Huerta, University of Illinois at Urbana-Champaign

Presentations by:

Tuesday, October 20

9:50 am
Eliu Huerta
10:00 am
Panel: Description of Our HDR Project: Vision, Mission, Accomplishments and Future Plans
Chair: Daniel S. Katz, University of Illinois at Urbana-Champaign

Philip Harris, MIT
Scott Hauck, University of Washington
Eliu Huerta, University of Illinois
Raffaella Margutti, Northwestern University
Patrick Brady, SCiMMA Project, University of Wisconsin-Milwaukee
11:30 am
An Ongoing Transformation: High Resolution Topography, AI, HPC and High-Resolution Imagery in the Geosciences
Chair: Sinan Deger, California Institute of Technology/IPAC

Paul Morin, Director, Polar Geospatial Center, University of Minnesota
The confluence of large volumes of readily accessible, high-resolution satellite observations, increasingly sophisticated software and continued growth in the capability of high-performance computing (HPC) now enable the production of high-demand, timely, high-quality, global-scale, geospatial products. Recent, highly successful partnerships have produced transformative geospatial products including the ArcticDEM, Reference Elevation Model of Antarctica (REMA), and the NASA Goddard Sahil Treecount Project, demonstrate the high return on investment achieved from providing collaborative teams of geospatial scientists and software engineers with access to large volumes of high resolution, high-frequency data, and efficient high-performance computing and services. Going forward, these projects offer the potential to deliver transformative new capabilities in the realms of artificial intelligence and machine learning, as well as efficient traditional methods, to dramatically improve the automated extraction of information from imagery over large areas and at high resolution and through time. Potentially, this will open an entirely new capability for a high-resolution understanding of a changing earth in many dimensions.
12:30 pm
1:30 pm
Exploring the Frontiers of Geospatial Data Science in the Era of AI and CyberGIS
Chair: Judith Hill, Oak Ridge National Lab

Shaowen Wang, Director, CyberGIS Center for Advanced Digital and Spatial Studies, University of Illinois at Urbana-Champaign
Geospatial data science represents an emerging interdisciplinary and transdisciplinary field intersecting among three broad knowledge domains: geospatial sciences and technologies, mathematical and statistical sciences, and cyberinfrastructure and computational sciences. The core of this intersection encompasses the synergies and interactions between AI, big data and cyberGIS (that is, geographic information science and systems based on advanced cyberinfrastructure) with geospatial principles guiding discovery and innovation. This presentation explores the frontiers of geospatial data science in the context of data-driven discovery and innovation. Several fundamental research problems are addressed while a set of challenges and opportunities are identified for synergistically advancing geospatial discovery and innovation. The presentation discusses how such advances are transforming data science education and research.
2:30 pm
3:00 pm
Applying Data Science in Business
Chair: Brendan McGinty, University of Illinois at Urbana-Champaign

Cory Glass, Director, Data Science at Phillips 66
4:00 pm
Illinois Institute for Data Science and Dynamical Systems (iDS2)
Chair: Zhizhen Zhao, University of Illinois at Urbana-Champaign

Maxim Raginsky, Srikant Rayadurgam, Niao He
Data science already exerts considerable influence over our everyday lives. As we move into the age of autonomous vehicles, smart cities, personalized medicine, and artificial intelligence, both data-driven algorithms and dynamical feedback loops will permeate every aspect of our lives. Therefore, there is a pressing need for a synthesis of data science and dynamical systems, including a clear-eyed assessment of both positive impacts and limitations. The research performed in iDS2 aims to lay the foundations for this synthesis. This overview talk will introduce the four research themes of the institute (Data modeling; Sampling and inference; Algorithm design; Decision-Making) and present the institute’s vision and ongoing projects that integrate ideas and techniques from control, optimization, statistics, and computer science to realize this vision.

Wednesday, October 21

8:50 am
Eliu Huerta
9:00 am –
11:00 am
Draft Plan of Engagement for the Fall 2020 and Spring 2021, Culminating in a Joint Proposal in the Spring 2021

NSF home This workshop is funded by the NSF through award NSF 1931561.

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