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Researcher
- Ahmed Hassen
- Vlastimil Kunc
- Steven Guzorek
- Rama K Vasudevan
- Ryan Dehoff
- Vipin Kumar
- Brian Post
- David Nuttall
- Sergei V Kalinin
- Yongtao Liu
- Dan Coughlin
- Kevin M Roccapriore
- Kyle Kelley
- Maxim A Ziatdinov
- Nadim Hmeidat
- Olga S Ovchinnikova
- Soydan Ozcan
- Steve Bullock
- Tyler Smith
- Adam Stevens
- Brittany Rodriguez
- Jim Tobin
- Kashif Nawaz
- Michael Kirka
- Pum Kim
- Segun Isaac Talabi
- Stephen Jesse
- Subhabrata Saha
- Sudarsanam Babu
- Uday Vaidya
- Umesh N MARATHE
- Vincent Paquit
- Alex Plotkowski
- Alex Roschli
- Alice Perrin
- Amir K Ziabari
- Amit Shyam
- An-Ping Li
- Andres Marquez Rossy
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Benjamin Lawrie
- Blane Fillingim
- Bogdan Dryzhakov
- Brian Fricke
- Chengyun Hua
- Christopher Ledford
- Christopher Rouleau
- Clay Leach
- Costas Tsouris
- Craig Blue
- Debangshu Mukherjee
- Erin Webb
- Evin Carter
- Gabor Halasz
- Georges Chahine
- Gerd Duscher
- Gs Jung
- Gyoung Gug Jang
- Halil Tekinalp
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilia N Ivanov
- Ivan Vlassiouk
- James Haley
- Jamieson Brechtl
- Jeremy Malmstead
- Jewook Park
- Jiaqiang Yan
- John Lindahl
- Jong K Keum
- Josh Crabtree
- Julian Charron
- Kai Li
- Katie Copenhaver
- Kim Sitzlar
- Kitty K Mccracken
- Komal Chawla
- Kyle Gluesenkamp
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Merlin Theodore
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Oluwafemi Oyedeji
- Ondrej Dyck
- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Petro Maksymovych
- Philip Bingham
- Radu Custelcean
- Rangasayee Kannan
- Roger G Miller
- Ryan Ogle
- Saban Hus
- Sai Mani Prudhvi Valleti
- Sana Elyas
- Sarah Graham
- Steven Randolph
- Sumner Harris
- Thomas Feldhausen
- Utkarsh Pratiush
- Venkatakrishnan Singanallur Vaidyanathan
- William Peter
- Xianhui Zhao
- Xiaobing Liu
- Yan-Ru Lin
- Ying Yang
- Yukinori Yamamoto
- 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.