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AI for Materials: From Discovery to Production

AI for Materials: From Discovery to Production

Tuesday, October 6 - Wednesday, October 7, 2020 EDT

The New York Academy of Sciences, 7 World Trade Center, 250 Greenwich St Fl 40, New York

Presented By

The New York Academy of Sciences

 

This Symposium aims for a broad perspective on leveraging the benefits of artificial intelligence (AI) in materials simulations, materials synthesis, and translating research into high-volume industrial production — covering the application of AI throughout the entire life cycle of new materials. It will bring together materials scientists, industry experts, and AI researchers to shape future research directions, identify urgent issues in this rising field, and foster interdisciplinary collaboration opportunities.

Call for Abstracts

Abstract submissions are invited for a poster session. For complete submission instructions, please visit our online portal. The deadline for abstract submission is Friday, August 28, 2020.

Call for Talks

Abstract submissions are invited for a series of 15-minute presentations. For complete submission instructions, please visit our online portal. The deadline for Contributed Talk submission is Friday, August 28, 2020.

Registration

Member
By 09/09/2020
$170
After 09/09/2020
$235
Nonmember Academia, Faculty, etc.
By 09/09/2020
$295
After 09/09/2020
$400
Nonmember Corporate, Other
By 09/09/2020
$365
After 09/09/2020
$495
Nonmember Not for Profit
By 09/09/2020
$295
After 09/09/2020
$400
Nonmember Student, Undergrad, Grad, Fellow
By 09/09/2020
$185
After 09/09/2020
$255
Member Student, Post-Doc, Fellow
By 09/09/2020
$135
After 09/09/2020
$185
Earlybird Registration:
107
days
left
Deadline:
95
days
left

Speakers

Leon Bottou
Léon Bottou, PhD

Facebook AI Research

Rampi Ramprasad
Rampi Ramprasad, PhD

Georgia Institute of Technology

Nobuyuki Matsuzawa
Nobuyuki Matsuzawa, PhD

Panasonic Corporation

Organizing Committee

Kristin Persson
Kristin Persson, PhD

UC Berkeley/Lawrence Berkeley National Laboratory

Anatoly Frenkel
Anatoly Frenkel, PhD

Brookhaven National Laboratory/Stony Brook University

Sergei Kalinin
Sergei V. Kalinin, PhD

Oak Ridge National Laboratory

Joshua Schrier
Joshua Schrier, PhD

Fordham University

Jennifer L. Costley, PhD
Jennifer L. Costley, PhD

The New York Academy of Sciences

Liang Dong, PhD
Liang Dong, PhD

The New York Academy of Sciences

Tuesday

October 06, 2020

8:15 AM

Breakfast and Registration

9:00 AM

Opening Remarks: The New York Academy of Sciences

Physics and Causality in Machine Learning

Session Chairperson
Payel Das, Sergei V. Kalinin
9:05 AM

Keynote Address

Speaker

Leon Bottou
Facebook
9:40 AM

Presentation Session #1

Speakers

Carla Gomes, PhD
Cornell University
Rama Vasudevan, PhD
Oak Ridge National Lab
10:30 AM

AM Coffee Break

11:00 AM

Presentation Session #2

12:10 PM

STAR* Talks

12:40 PM

Lunch

Data Infrastructures

Session Chairperson
Anatoly Frenkel, Kristin Persson
1:45 PM

Keynote Address

Speaker

Rampi Ramprasad, PhD
Georgia Tech
2:20 PM

Presentation Session #3

Speakers

Jason Hattrick-Simpers, PhD
National Institute of Standards and Technology (NIST)
Matthias Scheffler, PhD
FHI Berlin
3:10 PM

Poster Session & PM Coffee Break

4:00 PM

Presentation Session #4

Speaker

Tonio Buonassisi, PhD
MIT
5:10 PM

First Day Wrap Up

5:20 PM

Reception

6:30 PM

End of Day 1

Wednesday

October 07, 2020

8:00 AM

Breakfast and Registration

8:30 AM

Opening Remarks: The New York Academy of Sciences

AI in Materials Production and Industry

Session Chairperson
Mat Halls, Josh Schrier
8:35 AM

Materials Design in the Electronics Industry: Application of Materials Informatics and the Cloud Computing Environment to the Design of Organic Carrier Transport Materials

Speaker

Nobuyuki N. Matsuzawa, PhD
Panasonic Corporation

In addition to the boosting of CPU power due to the progress of semiconductor technology, the recent expansion of the cloud computing environment is inducing a huge impact on materials design based on computational chemistry by drastically increasing the number of candidate molecules that can be calculated within a reasonable timeframe.  Furthermore, rapid progress in the area of materials informatics (MI) is accelerating the speed of performing predictions of material properties; now a prediction can be made within milliseconds by MI, as compared to hours or even days by conventional computational methods.  This progress has enabled massive screening of millions of materials that might show desired properties.  Results of the progress of recent AI-related technologies are further being introduced to the area of materials development in the form of various proposals to realize the inverse materials design.

In this talk, results of our trials to introduce such progresses to the materials design in electronic industry will be presented for the case of the design of organic carrier transport materials such as heteroacenes.  Results of a quarter-million screenings of such materials using the cloud computing environment will be discussed in combination with the results of benchmark studies of various methods of inverse materials design, such as the use of junction-tree neural networks.

9:10 AM

Presentation Session #5

Speakers

Muratahan Aykol, PhD
Toyota Research Institute
Elsa Olivetti, PhD
MIT
10:00 AM

AM Coffee Break

10:30 AM

Panel Discussion: Closed Loop Production Through AI: Automating the Design, Build, Test, and Learn Cycle

11:20 AM

Presentation Session #6

Speaker

Michael Helander, PhD
OTI Lumionics
12:30 PM

Session Summaries

12:56 PM

Final Remarks: The New York Academy of Sciences

1:00 PM

End of Day 2