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Researcher
- Rama K Vasudevan
- Ryan Dehoff
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Kyle Kelley
- Maxim A Ziatdinov
- Olga S Ovchinnikova
- Yong Chae Lim
- Zhili Feng
- Jian Chen
- Kashif Nawaz
- Michael Kirka
- Peeyush Nandwana
- Rangasayee Kannan
- Stephen Jesse
- Vincent Paquit
- Wei Zhang
- Adam Stevens
- Ahmed Hassen
- Alex Plotkowski
- 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
- Brian Post
- Bryan Lim
- Chengyun Hua
- Christopher Ledford
- Christopher Rouleau
- Clay Leach
- Costas Tsouris
- Dali Wang
- David Nuttall
- Debangshu Mukherjee
- Gabor Halasz
- Gerd Duscher
- Gs Jung
- Gyoung Gug Jang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilia N Ivanov
- Ivan Vlassiouk
- James Haley
- Jamieson Brechtl
- Jewook Park
- Jiaqiang Yan
- Jiheon Jun
- 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
- Petro Maksymovych
- Philip Bingham
- Priyanshi Agrawal
- Radu Custelcean
- Roger G Miller
- Saban Hus
- Sai Mani Prudhvi Valleti
- Sarah Graham
- Steven Randolph
- Sudarsanam Babu
- Sumner Harris
- Tomas Grejtak
- Utkarsh Pratiush
- Venkatakrishnan Singanallur Vaidyanathan
- Vipin Kumar
- Vlastimil Kunc
- William Peter
- Xiaobing Liu
- Yan-Ru Lin
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto
- Zhiming Gao

This technology provides a device, platform and method of fabrication of new atomically tailored materials. This “synthescope” is a scanning transmission electron microscope (STEM) transformed into an atomic-scale material manipulation platform.

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.