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Researcher
- Omer Onar
- Subho Mukherjee
- Vivek Sujan
- Mostak Mohammad
- Vandana Rallabandi
- Rama K Vasudevan
- Erdem Asa
- Sergei V Kalinin
- Shajjad Chowdhury
- Yongtao Liu
- Adam Siekmann
- Burak Ozpineci
- Emrullah Aydin
- Jon Wilkins
- Kevin M Roccapriore
- Kyle Kelley
- Maxim A Ziatdinov
- Olga S Ovchinnikova
- Gui-Jia Su
- Isabelle Snyder
- Kashif Nawaz
- Stephen Jesse
- Veda Prakash Galigekere
- Ali Riza Ekti
- An-Ping Li
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Benjamin Lawrie
- Bogdan Dryzhakov
- Brian Fricke
- Chengyun Hua
- Christopher Rouleau
- Costas Tsouris
- Debangshu Mukherjee
- Gabor Halasz
- Gerd Duscher
- Gs Jung
- Gyoung Gug Jang
- Hong Wang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Hyeonsup Lim
- Ilia N Ivanov
- Ivan Vlassiouk
- Jamieson Brechtl
- Jewook Park
- Jiaqiang Yan
- Jong K Keum
- Kai Li
- Kyle Gluesenkamp
- Liam Collins
- Lingxiao Xue
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Nishanth Gadiyar
- Ondrej Dyck
- Petro Maksymovych
- Radu Custelcean
- Rafal Wojda
- Saban Hus
- Sai Mani Prudhvi Valleti
- Steven Randolph
- Sumner Harris
- Utkarsh Pratiush
- 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 invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.

The described concept provides a predictive technology solution to increase the safety of platooning vehicles.

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.

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.

ORNL has developed a revolutionary system for wirelessly transferring power to electric vehicles and energy storage systems, enabling efficient, contactless charging.
Aromas play a significant role in the quality and safety of food, beverages, and even manufactured products. The ability to detect and interpret these aromas accurately can enhance product safety and consumer satisfaction.