Ohio State nav bar

NSF I-AIM Project Kickoff Meeting : Interpretable Augmented Intelligence for Multiscale Material Discovery

Figures illustrating different material structures at small scales
October 25 - October 26, 2019
8:00AM - 5:00PM
MBI Auditorium, Jennings Hall 355 and The STEAM Factory, 400 W Rich St

Date Range
Add to Calendar 2019-10-25 08:00:00 2019-10-26 17:00:00 NSF I-AIM Project Kickoff Meeting : Interpretable Augmented Intelligence for Multiscale Material Discovery This is the kick-off meeting for the NSF project I-AIM : Interpretable Augmented Intelligence for Multiscale Material Discovery . The ultimate goal of NSF Harnessing Data Revolution (HDR) initiative is to create Data-Intensive Research in Science and Engineering (DIRSE). The I-AIM project is part of the Phase I of this initiative. During this project, a multi-disciplinary team will develop various research activities to support the conceptualization of a potential future Institute to use novel data science methods to address fundamental scientific questions of materials engineering and manufacturing. More specifically, this project aims to combine machine learning frameworks with uncertainty quantification and geometric/topological data analysis to advance the analysis of large sets of structural data of composite materials (e.g., polymer-carbon nanotubes (CNT) composites) and alloys from the atomic scale to correlate with and predict mechanical properties. We hope the resulting data-driven approaches can help uncover underlying structural features in the materials that determine the properties and performance, and help accelerate the development of ultra-high strength and lightweight carbon-based composites. The goal of this kickoff meeting is to provide a platform where the multidisciplinary team members, as well as several external experts can meet and share our vision for the project, as well as develop plans for this Phase I stage. The kickoff meeting will be held on October 25 and 26. The first day will focus on the introduction of the project, presentations from external experts, and poster sessions by team members. It will be held at MBI. The second day will focus on focused team discussion, tutorial, and team building activities. It will be held at the STEAM Factory. This project is part of the National Science Foundation's Harnessing the Data Revolution (HDR) Big Idea activity and is co-funded by the Division of Civil, Mechanical and Manufacturing Innovation. In addition to NSF support, this kickoff meeting is also co-sponsored by Mathematical Biosciences Institute and the STEAM Factory.   MBI Auditorium, Jennings Hall 355 and The STEAM Factory, 400 W Rich St Mathematical Biosciences Institute mbi-webmaster@osu.edu America/New_York public

This is the kick-off meeting for the NSF project I-AIM : Interpretable Augmented Intelligence for Multiscale Material Discovery . The ultimate goal of NSF Harnessing Data Revolution (HDR) initiative is to create Data-Intensive Research in Science and Engineering (DIRSE). The I-AIM project is part of the Phase I of this initiative. During this project, a multi-disciplinary team will develop various research activities to support the conceptualization of a potential future Institute to use novel data science methods to address fundamental scientific questions of materials engineering and manufacturing. More specifically, this project aims to combine machine learning frameworks with uncertainty quantification and geometric/topological data analysis to advance the analysis of large sets of structural data of composite materials (e.g., polymer-carbon nanotubes (CNT) composites) and alloys from the atomic scale to correlate with and predict mechanical properties. We hope the resulting data-driven approaches can help uncover underlying structural features in the materials that determine the properties and performance, and help accelerate the development of ultra-high strength and lightweight carbon-based composites.

The goal of this kickoff meeting is to provide a platform where the multidisciplinary team members, as well as several external experts can meet and share our vision for the project, as well as develop plans for this Phase I stage.

The kickoff meeting will be held on October 25 and 26. The first day will focus on the introduction of the project, presentations from external experts, and poster sessions by team members. It will be held at MBI. The second day will focus on focused team discussion, tutorial, and team building activities. It will be held at the STEAM Factory.

This project is part of the National Science Foundation's Harnessing the Data Revolution (HDR) Big Idea activity and is co-funded by the Division of Civil, Mechanical and Manufacturing Innovation. In addition to NSF support, this kickoff meeting is also co-sponsored by Mathematical Biosciences Institute and the STEAM Factory.

National Science Foundation logo
The Steam Factory logo

 

Schedule

Time Session
08:00 AM
08:30 AM
Breakfast and Meet and Greet
08:30 AM
08:45 AM
Vision and Welcome
08:45 AM
09:05 AM
Yusu Wang - Some Examples of Combining Topological Data Analysis (TDA) with Machine Learning
09:05 AM
09:35 AM
Steve Sun - Self-Derived Plasticity Models with Non-Euclidean Internal Variables
09:35 AM
09:55 AM
Wei Chen - Data-driven Discovery and Design of Engineering Alloys
09:55 AM
10:15 AM
Yanxun Xu - Incorporating Uncertainty Quantification in Deep Reinforcement Learning
10:15 AM
10:35 AM
Richard Liang - Tomography of Carbon Nanotube Sheets and Composites
10:35 AM
10:55 AM
Break
10:55 AM
11:15 AM
Hendrik Heinz - Computational Trajectories and Data for Carbon/Polymer Materials Property Predictions
11:15 AM
11:35 AM
Dhriti Nepal - Interphase Tailoring of Carbon Fiber with 1D and 2D Nanoparticles
11:35 AM
11:55 AM
Pedro Arias Monje and Narayan Shirolkar - Challenges in Carbon Fiber Analysis
11:55 AM
12:15 PM
Peter Liaw - High-Entropy Alloys
12:15 PM
12:35 PM
Gregory Odegard - US-COMP and Computational Property Prediction of CNT/Composites
12:35 PM
02:00 PM
Pizza Lunch at MBI
02:00 PM
02:30 PM
Michael Groeber and Steve Niezgoda
02:30 PM
02:45 PM
Breakout Sessions (Groups 1-3) - Aims: Work Plan, Data Flow from/to Collaborators
02:45 PM
03:45 PM
Work in Groups
03:45 PM
04:00 PM
Break
04:00 PM
04:30 PM
Report Out
04:30 PM
05:30 PM
Poster Session
06:00 PM
08:00 PM
Dinner
Time Session
09:00 AM
09:30 AM
Breakfast
09:30 AM
12:00 PM
Work Plan
Specific Tasks and Timelines for First 6 Months
Assignment of Specific Deliverables
Plan for First 1-2 Publications
Potential Issues
12:00 PM
01:30 PM
Lunch
01:30 PM
03:00 PM
Steve Tutorial
03:00 PM Wrap Up

 

 

Participants

Name Affiliation Email
Bahador Bahmani Columbia University  
Rajiv Berry Air Force Research Laboratory  
Cai Chen The Ohio State University chencai.math@gmail.com
Wei Chen Illinois Institute of Technology  
Michael Groeber The Ohio State University groeber.9@osu.edu
Hendrik Heinz University of Colorado Boulder hendrik.heinz@colorado.edu
Krishan Kanhaiya University of Colorado Boulder krishan.kanhaiya@colorado.edu
George Kim Illinois Institute of Technology  
Richard Liang Florida State University  
Peter Liaw University of Tennessee  
Lucas Magee The Ohio State University magee.113@buckeyemail.osu.edu
Pedro Arias Monje Georgia Institute of Technology  
Soham Mukherjee The Ohio State University mukherjee.126@buckeyemail.osu.edu
Dhriti Nepal Air Force Research Laboratory  
Steve Niezgoda The Ohio State University niezgoda.6@osu.edu
Gregory Odegard Michigan Technological University gmodegar@mtu.edu
Ruth Pachter Air Force Research Laboratory  
Ajit Roy Air Force Research Laboratory  
Narayan Shirolkar Georgia Institute of Technology  
Steve WaiChing Sun Columbia University wsun@columbia.edu
Xiao Sun Johns Hopkins University sxiao12@jhu.edu
Nikolas Vlassis Columbia University  
Yusu Wang The Ohio State University yusu@cse.ohio-state.edu
Jordan Winetrout University of Colorado Boulder jordan.winetrout@colorado.edu
Yanxun Xu Johns Hopkins University yanxun.xu@jhu.edu
Jie Zhang Illinois Institute of Technology  
Qi Zhao The Ohio State University zhao.2017@buckeyemail.osu.edu

 

 

Events Filters: