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Researcher
- Ryan Dehoff
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Kyle Kelley
- Maxim A Ziatdinov
- Olga S Ovchinnikova
- Venkatakrishnan Singanallur Vaidyanathan
- Vincent Paquit
- Amir K Ziabari
- Diana E Hun
- Kashif Nawaz
- Michael Kirka
- Philip Bingham
- Philip Boudreaux
- Stephen Jesse
- Stephen M Killough
- Adam Stevens
- Ahmed Hassen
- Alex Plotkowski
- Alice Perrin
- Amit Shyam
- An-Ping Li
- Andres Marquez Rossy
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Blane Fillingim
- Bogdan Dryzhakov
- Brian Fricke
- Brian Post
- Bryan Maldonado Puente
- Christopher Ledford
- Christopher Rouleau
- Clay Leach
- Corey Cooke
- Costas Tsouris
- David Nuttall
- Debangshu Mukherjee
- Gerd Duscher
- Gina Accawi
- Gs Jung
- Gurneesh Jatana
- Gyoung Gug Jang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilia N Ivanov
- Ivan Vlassiouk
- James Haley
- Jamieson Brechtl
- Jewook Park
- Jong K Keum
- Kai Li
- Kyle Gluesenkamp
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Mark M Root
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Nolan Hayes
- Obaid Rahman
- Ondrej Dyck
- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Peter Wang
- Radu Custelcean
- Rangasayee Kannan
- Roger G Miller
- Ryan Kerekes
- Saban Hus
- Sai Mani Prudhvi Valleti
- Sally Ghanem
- Sarah Graham
- Steven Randolph
- Sudarsanam Babu
- Sumner Harris
- Utkarsh Pratiush
- Vipin Kumar
- Vlastimil Kunc
- William Peter
- 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.

Technologies for optimizing prefab retrofit panel installation using a real-time evaluator is described.

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.