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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
- Vincent Paquit
- Andrzej Nycz
- Clay Leach
- Kashif Nawaz
- Kuntal De
- Michael Kirka
- Stephen Jesse
- Udaya C Kalluri
- Adam Stevens
- Ahmed Hassen
- Alex Plotkowski
- Alex Walters
- Alice Perrin
- Amir K Ziabari
- Amit Shyam
- An-Ping Li
- Andres Marquez Rossy
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Biruk A Feyissa
- Blane Fillingim
- Bogdan Dryzhakov
- Brian Fricke
- Brian Post
- Chris Masuo
- Christopher Ledford
- Christopher Rouleau
- Costas Tsouris
- David Nuttall
- Debangshu Mukherjee
- Debjani Pal
- Gerd Duscher
- Gs Jung
- 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
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Ondrej Dyck
- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Philip Bingham
- Radu Custelcean
- Rangasayee Kannan
- Roger G Miller
- Saban Hus
- Sai Mani Prudhvi Valleti
- Sarah Graham
- Singanallur Venkatakrishnan
- Steven Randolph
- Sudarsanam Babu
- Sumner Harris
- Utkarsh Pratiush
- Vipin Kumar
- Vlastimil Kunc
- William Peter
- Xiaobing Liu
- Xiaohan Yang
- Yan-Ru Lin
- Ying Yang
- Yukinori Yamamoto
- Zhiming Gao

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.

The invention provides a gene and methods for maintaining meiotic chromosomal architecture

An innovative system for automating the surveillance and manipulation of plant tissues using advanced machine vision and robotic tools.

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.

A high-strength, heat-resistant Al-Ce-Ni alloy optimized for additive manufacturing in industrial applications.