Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
As a part of the JARVIS workshop series, NIST is sponsoring the 5th Artificial Intelligence for Materials Science (AIMS) workshop. The workshop will be held in-person only at the National Cybersecurity Center of Excellence (NCCoE), located at 9700 Great Seneca Highway, Rockville, MD 20850, from July 17 - 18, 2024.
The Materials Genome Initiative (MGI) promises to expedite materials discovery through high-throughput computation and high-throughput experiments. The application of artificial-intelligence (AI) tools such as machine-learning, deep-learning and various optimization techniques is critical to achieving such a goal.
Some of the key research areas for materials AI include: developing well-curated and diverse datasets, choosing effective representations for materials, inverse materials design, integrating autonomous experiments and theory, merging physics-based models with AI models, and choosing appropriate algorithms/work-flows. Lastly, uncertainty quantification in AI-based predictions for material properties and issues related to building infrastructure for disseminating AI knowledge are of immense importance for making AI- based materials investigation successful. This workshop is intended to cover all the above-mentioned challenges. To make the workshop as effective as possible we plan to largely but not exclusively focus on inorganic solid-state materials.
Topics addressed in this workshop will include (but not be limited to):
1) Datasets and tools for employing AI for materials
2) Integrating experiments with AI techniques
3) Graph neural networks for materials
4) Comparison of AI techniques for materials
5) Challenges of applying AI to materials
6) Uncertainty quantification and building trust in AI predictions
7) Generative modeling
8) Using AI to develop classical force-fields
9) Natural language processing/Large language models
CALL FOR POSTERS
If registered participants are interested in presenting a poster, please send name, affiliation, title and abstract to daniel.wines [at] nist.gov (daniel[dot]wines[at]nist[dot]gov) no later than 5/31/2024.
CONFIRMED SPEAKERS
- Anouar Benali (Argonne National Lab)
- Ale Strachan (Purdue)
- Eddie Kim (Cohere)
- Tian Xie (Microsoft)
- Christopher Sutton (South Carolina)
- Hongliang Xin (Virginia Tech)
- Nicola Marzari (EPFL)
- Sergei Kalinin (University of TN, Knoxville, PNNL)
- Chris Stiles (JHUAPL)
- Yongqiang Cheng (ORNL)
- Mathew Cherukara (Argonne National Lab)
- Olga Wodo (University at Buffalo)
- Ming Hu (South Carolina)
- Keqiang Yan (TAMU)
- P. Ganesh (ORNL)
- Rama Vasudevan (ORNL)
- Guido von Rudorff (University of Kassel)
- Maria Chan (Argonne National Lab)
- Vidushi Sharma (IBM)
- Debra Audus (NIST)
- Dilpuneet Aidhy (Clemson)
- Michael Waters (Northwestern)
- Timur Bazhirov (Mat3ra)
- Anuroop Sriram (Meta)
co-organizers
- Daniel Wines
- Kamal Choudhary
- Francesca Tavazza
- Kevin Garrity
- Brian DeCost
- Howie Joress
- Austin McDannald
Start Time | End | Session Name/Information |
9:00am | 9:10am | Opening Remarks: Jim Warren |
9:10am | 9:25am | Overview and Logistics: Kamal Choudhary |
9:25am | 11:45am | Invited Session I Nicola Marzari: Machine Learning Electrochemistry P. Ganesh, Abdulgani Annaberdiyev: Predicting Quantum Monte Carlo Charge Densities using Graph Neural Networks Anouar Benali: Increasing AI/ML Predictions Through DMC-enhanced Delta Learning
Ming Hu: Unleashing the Power of Artificial Intelligence for Phonon Thermal Transport Christopher Sutton: Machine Learning Models for Accelerating Materials Discovery |
12:00pm | 1:00pm | Lunch |
| 1:00pm | 3:20pm | Invited Session II Sergei Kalinin: Integrating Autonomous Systems for Advanced Material Discovery: Bridging Experiments and Theory Through Optimized Rewards Mathew Cherukara: HPC+AI-enabled Materials Characterization and Experimental Automation Chris Stiles: Targeted AI-Driven Materials Discovery (Break: 2:00 - 2: 20pm) Rama Vasudevan: Algorithms and Opportunities for Self-Driving Laboratories: Model-Based Control, Physics Discovery, and Co-Navigating Theory and Experiments Maria Chan: Theory-Informed AI/ML for Materials Characterization Yongqiang Cheng: Data-driven Approaches to Lattice Dynamics and Vibrational Spectroscopy |
| 3:20pm | 4:00pm | Panel Discussion Moderator: Brian DeCost Sergei Kalinin, Hongliang Xin, Chris Stiles, Rama Vasudevan, Maria Chan, Vidushi Sharma, Timur Bazhirov |
| 4:00pm | 5:30pm | Poster Session |
Start Time | End | Session Name/Information |
8:45am | 11:45pm | Invited Session III Tian Xie: Accelerating Materials Design with AI Emulators and Generators Vidushi Sharma: Chemical Foundation Models for Complex Materials Eddie Kim: A Practical Guide to Building with LLMs Anuroop Sriam: Beyond Experimental Structures: Advancing Materials Discovery with Generative AI Break (10:05-10:25) Timur Bazhirov: Data Standards: The Key Enabler of AI-Driven Materials Science at the Nanoscale Ale Strachan: Combining Machine-Learning, Physics, and Infrastructure to Accelerate Materials Research Debra Audus: Improving Machine Learning with Polymer Physics Dilpuneet Aidhy: Integrated Data Science and Computational Materials Science in Complex Materials |
12:00pm | 1:00pm | Lunch |
1:00pm | 2:20pm | Invited Session IV Michael Waters: Sampling Strategies for Robust MLIPs Guido von Rudorff: Unbiased Sampling of Chemical Space Olga Wodo: Data-driven Microstructure-Property Mapping: the Importance of Microstructure Representation Keqiang Yang: Artificial Intelligence for Materials Geometric Representation Learning and High Tensor Order Property Predictions |
2:30pm | 4:15pm | Hands-on Session Peter Bajcsy, Austin McDannald, Brain DeCost, Daniel Wines, Kamal Choudhary |
Hotel Room Block
We have booked a room block at the following location:
Hotel: DoubleTree by Hilton Washington DC North/Gaithersburg
Address: 620 Perry Parkway, Gaithersburg, MD 20877
Rate: $139/person plus tax. Rate includes transportation to and from NCCoE for both days of the conference.
Last day to book: July 8, 2024
CLICK HERE to book your room.
*Visitor Access Requirement:
For Non-US Citizens: Please have your valid passport for photo identification.
For US Permanent Residents: Please have your green card for photo identification.
For US Citizens: Please have your state-issued driver's license. Regarding Real-ID requirements, all states are in compliance or have an extension through May 2025.
NIST also accepts other forms of federally issued identification in lieu of a state-issued driver's license, such as a valid passport, passport card, DOD's Common Access Card (CAC), Veterans ID, Federal Agency HSPD-12 IDs, and Military Dependents ID.