Plenary, breakout, hackathon, and tutorial topics and speakers are TBD as per TPC Steering and Program Committees, and will be announced over the coming months.
Monday, July 28
9:00
Hackathon Opening Plenary
Rick Stevens, Argonne National Laboratory
Tutorial Opening Plenary
Neeraj Kumar, Pacific Northwest National Laboratory
9:30
Break
10:00
Hackathon Sessions 1
Tutorial Sessions 1
Evaluation of AI Model Scientific Reasoning Skills
AI for Science Part I: The Basics
11:15
Break
11:45
Hackathon Sessions 2
Tutorial Sessions 2
Evaluation of AI Model Scientific Reasoning Skills
AI for Science Part I: The Basics (cont)
13:00
Lunch
14:30
Hackathon Sessions 3
Tutorial Sessions 3
Evaluation of AI Model Scientific Reasoning Skills
AI for Science Part II: Applications
15:45
Break
16:15
Hackathon Sessions 4
Tutorial Sessions 4
Evaluation of AI Model Scientific Reasoning Skills
AI for Science Part II: Applications (cont)
17:30
Break
18:00 – 19:30
Hackathon Gathering
Tuesday, July 29
9:00
Hackathon Sessions 5
Tutorial Sessions 1
AI for Science Part III: Advanced Topics
Exhibition
10:15
Break
EXHBITION
10:45
Hackathon Sessions 6
Tutorial Sessions 2
AI for Science Part III: Advanced Topics (cont)
Exhibition
12:00
Hackathon Closing Plenary
Miguel Vazquez, Barcelona Supercomputing Center
Break
Exhibition
12:30
Lunch
EXHBITION
14:00
Opening Plenary
Welcome and TPC Keynote: SCALING UP TO GW DATA CENTERS AND AI FACTORIES
Rick Stevens, Argonne National Laboratory
Welcome Keynote:
Thierry Pellegrino, AWS
EXHBITION
15:30
BREAK
EXHBITION
16:00
Reinventing HPC: AI Inference, Training, and Other Services
Moderator: Satoshi Matsuoka, REIKEN
Keynote
Invited Speaker 1
Invited Speaker 2
Invited Speaker 3
EXHBITION
17:30
BREAK
EXHBITION
18:00 – 19:30
Welcome Reception
Wednesday, July 30
9:00
Agentic Systems, Multimodal Data, and Non-LLM Model Architectures
Moderator: Ian Foster, Argonne National Laboratory
Keynote
Prasanna Balaprakash, Oak Ridge National Laboratory, USA
Flora Salim, University of New South Wales, Australia
Invited Speaker 3
EXHBITION
10:30
Break
EXHBITION
11:00
Evaluation of AI Systems: Performance, Skills, Trust
Moderator: Ricardo Baeza-Yates, Barcelona Supercomputing Center
Keynote
Rio Yokota, Tokyo Institute of Technology, Japan
Franck Cappello, Argonne National Laboratory, USA
Invited Speaker 3
EXHBITION
12:30
Lunch
EXHBITION
14:00
Parallel Breakouts A
Job Fair
EXHBITION
15:30
Break
EXHBITION
16:00
Parallel Breakouts B
Job Fair
EXHBITION
Thursday, July 31
9:00
Parallel Breakouts C
10:30
Break
11:00
Parallel Breakouts D
12:30
LUNCH
Panel Discussion – Industry, Academia, and Government Collaboration: Accelerating Responsible AI for Science
Moderator: Karthik Duraisamy, University of Michigan
14:00
Parallel Breakouts E
15:30
Break
16:00
CLOSING PLENARY SESSION
Moderator: Charlie Catlett, Argonne National Laboratory
Plenary, breakout, hackathon, and tutorial topics and speakers are TBD as per TPC Steering and Program Committees, and will be announced over the coming months. Some of TPC’s prior speakers include:
Ian Foster, one of the 10 most cited computer scientists in the U.S. His work in “Grid Computing” began in 1994 and provided much of the underlying principles that were applied a decade later to create cloud computing. His team’s distributed computing infrastructure, Globus, is used by hundreds of computing centers around the world for both traditional scientific HPC computing and for AI workflows.
Rick Stevens, who is responsible for Argonne’s HPC center and a portfolio of over $500M/year of research. He has been one of the leaders in the DOE community that laid the intellectual and funding groundwork for the multi-$B Exascale project and the multi-$B plan for DOE investment in AI.
Satoshi Matsuoka, Japan’s leading computational scientist, with a portfolio and responsibilities at Japan’s RIKEN national laboratory similar to Rick Stevens’ programs at Argonne. He has won numerous international leadership awards and received an award from the Emperor of Japan for his work computational modeling of COVID-19 spread, which saved lives through its use designing public health policies during the pandemic.