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Researcher
- Soydan Ozcan
- Meghan Lamm
- Rama K Vasudevan
- Halil Tekinalp
- Sergei V Kalinin
- Umesh N MARATHE
- Vlastimil Kunc
- Yongtao Liu
- Ahmed Hassen
- Katie Copenhaver
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Steven Guzorek
- Uday Vaidya
- Alex Roschli
- Beth L Armstrong
- Dan Coughlin
- Georges Chahine
- Kyle Kelley
- Matt Korey
- Pum Kim
- Vipin Kumar
- Adwoa Owusu
- Akash Phadatare
- Amber Hubbard
- Anton Ievlev
- Arpan Biswas
- Ben Lamm
- Brian Post
- Cait Clarkson
- David Nuttall
- Erin Webb
- Evin Carter
- Gabriel Veith
- Gerd Duscher
- Jeremy Malmstead
- Jesse Heineman
- Jim Tobin
- Josh Crabtree
- Khryslyn G Araño
- Kim Sitzlar
- Kitty K Mccracken
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marm Dixit
- Marti Checa Nualart
- Nadim Hmeidat
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Oluwafemi Oyedeji
- Paritosh Mhatre
- Sai Mani Prudhvi Valleti
- Sana Elyas
- Sanjita Wasti
- Segun Isaac Talabi
- Shajjad Chowdhury
- Stephen Jesse
- Steve Bullock
- Sumner Harris
- Tolga Aytug
- Tyler Smith
- Utkarsh Pratiush
- Xianhui Zhao

This invention demonstrates the strong potential for hybridization of CNF with natural fibers for facile drying and inclusion of the CNF into polymer matrices for high performance composites.

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.

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.