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Researcher
- Peeyush Nandwana
- Rama K Vasudevan
- Ryan Dehoff
- Sergei V Kalinin
- Yongtao Liu
- Blane Fillingim
- Brian Post
- Kevin M Roccapriore
- Kyle Kelley
- Maxim A Ziatdinov
- Olga S Ovchinnikova
- Rangasayee Kannan
- Sudarsanam Babu
- Amit Shyam
- Kashif Nawaz
- Lauren Heinrich
- Michael Kirka
- Stephen Jesse
- Thomas Feldhausen
- Vincent Paquit
- Ying Yang
- Yousub Lee
- Adam Stevens
- Ahmed Hassen
- Alex Plotkowski
- Alice Perrin
- Amir K Ziabari
- An-Ping Li
- Andres Marquez Rossy
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Bogdan Dryzhakov
- Brian Fricke
- Bruce A Pint
- Bryan Lim
- Christopher Fancher
- Christopher Ledford
- Christopher Rouleau
- Clay Leach
- Costas Tsouris
- David Nuttall
- Debangshu Mukherjee
- Gerd Duscher
- Gordon Robertson
- Gs Jung
- Gyoung Gug Jang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilia N Ivanov
- Ivan Vlassiouk
- James Haley
- Jamieson Brechtl
- Jay Reynolds
- Jeff Brookins
- Jewook Park
- Jong K Keum
- Kai Li
- Kyle Gluesenkamp
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Ondrej Dyck
- Patxi Fernandez-Zelaia
- Peter Wang
- Philip Bingham
- Radu Custelcean
- Roger G Miller
- Saban Hus
- Sai Mani Prudhvi Valleti
- Sarah Graham
- Singanallur Venkatakrishnan
- Steven J Zinkle
- Steven Randolph
- Sumner Harris
- Tim Graening Seibert
- Tomas Grejtak
- Utkarsh Pratiush
- Vipin Kumar
- Vlastimil Kunc
- Weicheng Zhong
- Wei Tang
- William Peter
- Xiang Chen
- Xiaobing Liu
- Yan-Ru Lin
- Yanli Wang
- Yiyu Wang
- Yukinori Yamamoto
- Yutai Kato
- Zhiming Gao

In scientific research and industrial applications, selecting the most accurate model to describe a relationship between input parameters and target characteristics of experiments is crucial.

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

This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.

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

This invention introduces a system for microscopy called pan-sharpening, enabling the generation of images with both full-spatial and full-spectral resolution without needing to capture the entire dataset, significantly reducing data acquisition time.

An innovative low-cost system for in-situ monitoring of strain and temperature during directed energy deposition.

This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.

This technology introduces an advanced machine learning approach for enhancing chemical imaging by correlating data from two mass spectrometry imaging (MSI) techniques.