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Researcher
- Amit Shyam
- Alex Plotkowski
- Srikanth Yoginath
- Chad Steed
- James A Haynes
- James J Nutaro
- Junghoon Chae
- Peeyush Nandwana
- Pratishtha Shukla
- Rangasayee Kannan
- Ryan Dehoff
- Soydan Ozcan
- Sudip Seal
- Sumit Bahl
- Travis Humble
- Xianhui Zhao
- Adam Stevens
- Alex Roschli
- Alice Perrin
- Ali Passian
- Andres Marquez Rossy
- Annetta Burger
- Brian Post
- Bryan Lim
- Carter Christopher
- Chance C Brown
- Christopher Fancher
- Dali Wang
- Dean T Pierce
- Debraj De
- Erin Webb
- Evin Carter
- Gautam Malviya Thakur
- Gerry Knapp
- Gordon Robertson
- Halil Tekinalp
- Harper Jordan
- James Gaboardi
- Jay Reynolds
- Jeff Brookins
- Jeremy Malmstead
- Jesse McGaha
- Jian Chen
- Joel Asiamah
- Joel Dawson
- Jovid Rakhmonov
- Kevin Sparks
- Kitty K Mccracken
- Liz McBride
- Mengdawn Cheng
- Nance Ericson
- Nicholas Richter
- Oluwafemi Oyedeji
- Pablo Moriano Salazar
- Paula Cable-Dunlap
- Peter Wang
- Roger G Miller
- Samudra Dasgupta
- Sanjita Wasti
- Sarah Graham
- Sudarsanam Babu
- Sunyong Kwon
- Todd Thomas
- Tomas Grejtak
- Tyler Smith
- Varisara Tansakul
- Wei Zhang
- William Peter
- Xiuling Nie
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto
- Zhili Feng

We have developed a novel extrusion-based 3D printing technique that can achieve a resolution of 0.51 mm layer thickness, and catalyst loading of 44% and 90.5% before and after drying, respectively.

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

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.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

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.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

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