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Researcher
- Ryan Dehoff
- Blane Fillingim
- Brian Post
- Peeyush Nandwana
- Sudarsanam Babu
- Lauren Heinrich
- Michael Kirka
- Thomas Feldhausen
- Vincent Paquit
- Yousub Lee
- Adam Siekmann
- Adam Stevens
- Ahmed Hassen
- Alex Plotkowski
- Alice Perrin
- Amir K Ziabari
- Amit Shyam
- Andres Marquez Rossy
- Christopher Ledford
- Clay Leach
- David Nuttall
- Hong Wang
- Hyeonsup Lim
- James Haley
- Patxi Fernandez-Zelaia
- Philip Bingham
- Ramanan Sankaran
- Rangasayee Kannan
- Roger G Miller
- Sarah Graham
- Singanallur Venkatakrishnan
- Vimal Ramanuj
- Vipin Kumar
- Vivek Sujan
- Vlastimil Kunc
- Wenjun Ge
- William Peter
- Yan-Ru Lin
- Ying Yang
- Yukinori Yamamoto

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

Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.

High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.

Ceramic matrix composites are used in several industries, such as aerospace, for lightweight, high quality and high strength materials. But producing them is time consuming and often low quality.

In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.

Pairing hybrid neural network modeling techniques with artificial intelligence, or AI, controls has resulted in a unique hybrid system that creates a smart solution for traffic-signal timing.

This technology combines 3D printing and compression molding to produce high-strength, low-porosity composite articles.

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.