Breakout Sessions – AIRES 3 « Artificial Intelligence for Robust Engineering & Science @ Oak Ridge National Laboratory

Knowledge-informed Learning 1: Natural and Biological Systems
Knowledge-informed Learning 1: Natural and Biological Systems

The focus of this session is on identifying challenges associated with learning and building robust, accurate knowledge-informed digital twins of natural and biological systems. Potential applications where such capabilities may be relevant include personalized health, gaining insights into large-scale natural systems, and improving predictive capability and decision making in environmental systems, including climate systems. Topics of interest include but are not limited to the creation of the digital twin, data and validation needs, assurance requirements, and technology and infrastructure needs specific to natural and biological systems.

On-site Chair: Jeph Wang, Los Alamos National Laboratory

Virtual Chair: Amanda Howard. Pacific Northwest National Laboratory

Participant Assignments:
- Belinda Akpa
- Joseph Bakarji
- Yanzhao Cao
- Eric Church
- Warren Davis
- Kate Evans
- Rahul Ghosh
- Adi Hanuka
- Ben Hodges
- Forrest Hoffman
- Satish Karra
- Vipin Kumar
- Bing Li
- Po-Lun Ma
- Julie Mitchell
- David Najera-Flores
- Grace Peng
- Paris Perdikaris
- Christopher Rackauckas
- Juan Restrepo
- Balwinder Singh
- Kris Villez
- Aaron Young
Knowledge-informed Learning 2: Complex Engineered Systems
Knowledge-informed Learning 2: Complex Engineered Systems

The focus of this session is on identifying challenges associated with learning and building robust, accurate knowledge-informed digital twins of engineered systems. Potential applications include design optimization or automating control in complex engineered systems. Topics of interest include but are not limited to the creation of the digital twin, data and validation needs, assurance requirements, and technology and infrastructure needs specific to complex engineered systems.

On-site Chairs: Nat Trask and Carianne Martinez, Sandia National Laboratories

Virtual Chair: Malachi Schram, Jefferson Lab

Participant Assignments:
- Mihai Anitescu
- Craig Bakker
- Thomas Britton
- Michael Buche
- Matteo Corbetta
- Jana Doppa
- Urban Fasel
- Zhili Feng
- Olga Fink
- Brennan Harris
- Prashant Jain
- Ethan King
- Sharlotte Kramer
- Chetan Kulkarni
- Achalesh Kumar
- Bob Ledoux
- Steven Lee
- Diana McSpadden
- George Muntean
- Kristian Myhre
- Pinaki Pal
- Michael Parks
- Kishansingh Rajput
- Vivek Rathod
- Isabel Scherl
- Kshitij Tayal
- Chris Tennant
- Hoang Tran
- John Vickers
- Dali Wang
- Wesley Williams
- David Womble
- Srikanth Yoginath
- Huafeng Yu
- Yigit Yucesan
- Shukui Zhang
Assurance 1: Uncertainty Quantification
Assurance 1: Uncertainty Quantification

The goal of this session is to assess the landscape of uncertainty quantification and identify data needs, challenges in developing UQ methods to improve digital twin assurance and demonstration needs for UQ. The session will also attempt to identify aspects of AI and UQ relative to digital twins that may be missing from the existing scientific dialogue.

On-site Chair: Guannan Zhang, Oak Ridge National Laboratory

Virtual Chair: Daniel Ratner, SLAC National Accelerator Laboratory

Participant Assignments:
- Zhao Chen
- Agniva Chowdhury
- John Emery
- Hal Finkel
- Ryan King
- Dan Lu
- Stephan Mandt
- Himanshu Sharma
- Somya Sharma
- Wenceslao Shaw Cortez
- Vladimir Sobes
- Nan Wang
- Justin Weinmeister
Assurance 2: Trusted AI
Assurance 2: Trusted AI

This session will focus on the needs and challenges associated with trustworthy AI as part of digital twins. Topics for discussion include but are not limited to the state of the art within trustworthy AI, priority components necessary for achieving trustworthy digital twins, reliability, robustness, causal analysis, and explainability.

On-site Chair: David Stracuzzi, Sandia National Laboratories

Virtual Chair: Abhinav Saxena, GE Global Research

Participant Assignments:
- Samrat Chatterjee
- Dong Chen
- Jamie Coble
- David Etim
- Reese Jones
- Daniel Ju
- Markos Katsoulakis
- Farinaz Koushanfar
- Mihaela Quirk
- Pradeep Ramuhalli
- Jaideep Ray
- Jeremy Renshaw
- Saiph Savage
- Thiago Seuaciuc-Osorio
- Vaibhav Yadav
- Shaoming Xu
Edge Deployment and Co-design 1: AI and Models for Speed and Power Efficiency
Edge Deployment and Co-design 1: AI and Models for Speed and Power Efficiency

This session will explore deployment issues for AI and other models supporting digital twins, from the point of view of speed and power efficiency. Relevant architectures for edge deployment that meet or could address the deployment speed and power efficiencies, and integration approaches for hardware, algorithms, and data are among the topics of interest.

On-site Chair: Sudip Seal, Oak Ridge National Laboratory

Virtual Chair: Michael Churchill, Princeton Plasma Physics Laboratory

Participant Assignments:
- Ahmedullah Aziz
- Mehmet Belviranli
- Lance Drouet
- Mariana Fazio
- Yucheng Fu
- Shantenu Jha
- Frank Liu
- Massimiliano Lupo Pasini
- Narasinga Rao Miniskar
- Le Phan
- Majdi Radaideh
- Sibendu Som
- Panos Stinis
- Junxuan Zhao
Edge Deployment and Co-design 2: Workflow and Integrated HPC with Edge Deployment
Edge Deployment and Co-design 2: Workflow and Integrated HPC with Edge Deployment

This session will explore the workflow and scalability/integration aspects of edge deployment and co-design of AI for digital twins. Included in these are needs for research facilities and testbeds for validation and assurance, challenges associated with integrating HPC with edge deployment, and infrastructure requirements.

On-site Chair: Jibonananda Sanyal, National Renewable Energy Laboratory

Virtual Chair: Draguna Vrabie, Pacific Northwest National Laboratory

Participant Assignments:
- Elke Arenholz
- Sandra Biedron
- Willem Blokland
- Kevin Cao
- Gabe Fierro
- Christopher Garasi
- Dirk Hartmann
- Bryan Maldonado
- Ben Mintz
- Ravi Patel
- David Schmidt
- Jaiming Song
- Salvador Sosa Guitron