CMU/RX/AFOSR Joint Workshop at the Intersection of Materials Science and Machine Learning

July 19-21, 2023

9:00 a.m. - 5:00 p.m. ET

UES, Inc. conference room, 4401 Dayton-Xenia Rd, Dayton, OH

Thank you to all who attended this event. Presentations are available for select sessions as indicated below. 

The Center of Excellence on Data-Driven Discovery of Multifunctional Materials Systems is hosting a workshop on the current challenges and opportunities for machine learning in the context of material design and fabrication.

The workshop is intended for researchers at all levels and will feature contributors from academia, industry and government. The goal of the workshop is to identify future research topics where collaborations between Materials Science and Machine Learning have a unique advantage over separate efforts. We will be highlighting a range of potential topics, including consensus equilibrium and steady state microstructure evolution, equivariance in physics informed networks involving crystallographic symmetry, decision science and the next most informative sequence of experiments, as well as large language models in materials synthesis and applications. The workshop is not limited to just these topics: any new collaborative idea is welcome to the discussion. Participants in the workshop will learn about the fundamental and practical aspects of machine learning as they relate to applications in materials engineering. 

There is no fee for registration, but an RSVP is required.


Wednesday, July 19, 2023

Introductory talks

8:45 a.m. - 9:00 a.m. - Jeff Simmons, AFRL/RXNM (view presentation)
9:00 a.m. - 9:15 a.m. - Michael Bockstaller, Carnegie Mellon University (view presentation)
9:15 a.m. - 9:30 a.m. - Fariba Fahroo, AFRL/AFOSR

Keynote talk

9:45 a.m. - 10:45 a.m. - Reeja Jayan, Carnegie Mellon University (view presentation)

Poster Session

10:45 a.m. - 12:00 p.m. - College of Engineering Student Presentations


Session 1: Consensus Equilibrium and Steady State Behavior

1:00 p.m. - 1:45 p.m. - Hilmar Koerner, AFRL/RXNP (view presentation)
1:45 p.m. - 2:30 p.m. - Amanda Krause, Carnegie Mellon University 
2:30 p.m. - 2:45 p.m. - Break
2:45 p.m. - 3:30 p.m.  - Charlie Boumann, Greg Buzzard, Purdue University (view presentation)
3:30 p.m. - 4:30 p.m. - Discussion (Led by Eddie Schwalbach and Larry Drummy)


5:00 p.m. - Food and drinks available for purchase at Wandering Griffin (3725 Presidential Dr, Beavercreek, OH 45324)

Thursday, July 20, 2023

Session 2: Equivariance in Machine Learning for Physical Systems Involving Crystallographic Symmetry

8:30 a.m. - 9:15 a.m. - Kaushik Bhattacharya (view presentation)
9:15 a.m. - 10:00 a.m. - Marc DeGraef, Carnegie Mellon University (view presentation)
10:00 a.m. - 10:15 a.m. - Break
10:15 a.m. - 11:00 a.m. - Ulugbek Kamilov (view presentation)
11:00 a.m. - 12:00 p.m. - Discussion (Led by Sean Donegan and Paul Shade)


Session 3:  Decision Science and the Next Most Informative Sequence of Experiments

1:00 p.m. - 1:45 p.m. - Matt Cherry, Tyler Lesthaeghe (AFRL/RXNW, UDRI)
1:45 p.m. - 2:30 p.m. - Kristofer Reyes, University of Buffalo
2:30 p.m. - 2:45 p.m. - Break
2:45 p.m. - 3:30 p.m. - Aarti Singh, Carnegie Mellon University (view presentation)
3:30 p.m. - 4:30 p.m. - Discussion (Led by Mike Uchic and Benji Marayuma)


5:00 p.m. - Food and drinks available for purchase at Eudora
(3022 Wilmington Pike, Dayton, OH 45429)

Friday, July 21, 2023

Session 4: DoD and DoD related careers in the materials/machine learning ecosystem (technical talks of choice)

9:00 a.m. - 9:30 a.m.- Vince Monardo, MIT (view presentation)
9:30 a.m. - 10:00 a.m. - Brian DeCost, NIST
10:00 a.m. -10:15 a.m. - Break
10:15 a.m. - 10:45 a.m. - Eric Harper, AFRL/RXEP
10:45 a.m. - 11:15 a.m. - Sara Clements, Pratt & Whitney
11:15 a.m. - 12:00 p.m. - Discussion (Led by Lisa Rueschhoff and Andrew Gillman)

Break/Lunchtime Talk 

12:00 p.m. - 12:30 p.m. - Break and get lunch 
12:30 p.m. - 1:30 p.m. -  Lunchtime Talk with Gabe Gomes, Carnegie Mellon UniversityEmergent scientific experimentation capabilities of large language models

Optional Tours at WPAFB, AFRL/RX - Bldg 653

2:15 p.m. - 4:15 p.m. - Tours (You must be on a registered list of attendees to attend.)


The Data-Driven Discovery of Multifunctional Materials Systems Center of Excellence is a joint effort between Carnegie Mellon University and Air Force Research Laboratory directorates: Materials and Manufacturing Directorate and the Air Force Office of Scientific Research.