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Researcher
- Brian Post
- Peter Wang
- Andrzej Nycz
- Blane Fillingim
- Chris Masuo
- Peeyush Nandwana
- Srikanth Yoginath
- Sudarsanam Babu
- Thomas Feldhausen
- Ahmed Hassen
- Chad Steed
- J.R. R Matheson
- James J Nutaro
- Joshua Vaughan
- Junghoon Chae
- Lauren Heinrich
- Pratishtha Shukla
- Rangasayee Kannan
- Stephen M Killough
- Sudip Seal
- Travis Humble
- Yousub Lee
- Adam Stevens
- Alex Roschli
- Ali Passian
- Amit Shyam
- Brian Gibson
- Bryan Lim
- Bryan Maldonado Puente
- Cameron Adkins
- Christopher Fancher
- Chris Tyler
- Corey Cooke
- Craig Blue
- David Olvera Trejo
- Diana E Hun
- Gordon Robertson
- Harper Jordan
- Isha Bhandari
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- Joel Asiamah
- Joel Dawson
- John Lindahl
- John Potter
- Liam White
- Luke Meyer
- Michael Borish
- Nance Ericson
- Nolan Hayes
- Pablo Moriano Salazar
- Philip Boudreaux
- Ritin Mathews
- Roger G Miller
- Ryan Dehoff
- Ryan Kerekes
- Sally Ghanem
- Samudra Dasgupta
- Sarah Graham
- Scott Smith
- Steven Guzorek
- Tomas Grejtak
- Varisara Tansakul
- Vlastimil Kunc
- William Carter
- William Peter
- Yiyu Wang
- Yukinori Yamamoto

This manufacturing method uses multifunctional materials distributed volumetrically to generate a stiffness-based architecture, where continuous surfaces can be created from flat, rapidly produced geometries.

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.

Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.

The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.

QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.

A valve solution that prevents cross contamination while allowing for blocking multiple channels at once using only one actuator.

Materials produced via additive manufacturing, or 3D printing, can experience significant residual stress, distortion and cracking, negatively impacting the manufacturing process.

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.