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Researcher
- Ryan Dehoff
- Michael Kirka
- Vincent Paquit
- Yaosuo Xue
- Adam Stevens
- Ahmed Hassen
- Alex Plotkowski
- Alice Perrin
- Amir K Ziabari
- Amit Shyam
- Andres Marquez Rossy
- Blane Fillingim
- Brian Post
- Christopher Ledford
- Clay Leach
- Dali Wang
- David Nuttall
- Fei Wang
- James Haley
- Jian Chen
- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Phani Ratna Vanamali Marthi
- Philip Bingham
- Rafal Wojda
- Rangasayee Kannan
- Roger G Miller
- Sarah Graham
- Sreenivasa Jaldanki
- Sudarsanam Babu
- Suman Debnath
- Sunil Subedi
- Venkatakrishnan Singanallur Vaidyanathan
- Vipin Kumar
- Vlastimil Kunc
- Wei Zhang
- William Peter
- Yan-Ru Lin
- Ying Yang
- Yonghao Gui
- Yukinori Yamamoto
- Zhili Feng

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

Measurements of grid voltage and current are essential for the optimal operation of the grid protection and control (P&C) systems.

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

Multi-terminal DC (MTdc) systems based on high-voltage DC (HVDC) transmission technology is an upcoming concept. In such systems, either asymmetric monopole or bi-pole systems are generally employed. Such systems are not suitable for easy expansion.

Stability performance of interconnected power grids plays crucial roles on their secure operation to prevent cascading failure and blackout.

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.

Technologies directed to a multi-port autonomous reconfigurable solar power plant are described.

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.