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Researcher
- Peeyush Nandwana
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Kyle Kelley
- Maxim A Ziatdinov
- Olga S Ovchinnikova
- Amit Shyam
- Blane Fillingim
- Brian Post
- Kashif Nawaz
- Lauren Heinrich
- Rangasayee Kannan
- Stephen Jesse
- Sudarsanam Babu
- Thomas Feldhausen
- Yousub Lee
- Alex Plotkowski
- An-Ping Li
- Andres Marquez Rossy
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Benjamin Lawrie
- Bogdan Dryzhakov
- Brian Fricke
- Bruce A Pint
- Bryan Lim
- Chengyun Hua
- Christopher Fancher
- Christopher Rouleau
- Costas Tsouris
- Dali Wang
- Debangshu Mukherjee
- Gabor Halasz
- Gerd Duscher
- Gordon Robertson
- Gs Jung
- Gyoung Gug Jang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilia N Ivanov
- Ivan Vlassiouk
- Jamieson Brechtl
- Jay Reynolds
- Jeff Brookins
- Jewook Park
- Jian Chen
- Jiaqiang Yan
- 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
- Peter Wang
- Petro Maksymovych
- Radu Custelcean
- Ryan Dehoff
- Saban Hus
- Sai Mani Prudhvi Valleti
- Steven J Zinkle
- Steven Randolph
- Sumner Harris
- Tim Graening Seibert
- Tomas Grejtak
- Utkarsh Pratiush
- Weicheng Zhong
- Wei Tang
- Wei Zhang
- Xiang Chen
- Yanli Wang
- Ying Yang
- Yiyu Wang
- Yutai Kato
- Zhili Feng
- Zhiming Gao

Dual-GP addresses limitations in traditional GPBO-driven autonomous experimentation by incorporating an additional surrogate observer and allowing human oversight, this technique improves optimization efficiency via data quality assessment and adaptability to unanticipated exp

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

The invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.

High coercive fields prevalent in wurtzite ferroelectrics present a significant challenge, as they hinder efficient polarization switching, which is essential for microelectronic applications.

Scanning transmission electron microscopes are useful for a variety of applications. Atomic defects in materials are critical for areas such as quantum photonics, magnetic storage, and catalysis.

Distortion in scanning tunneling microscope (STM) images is an unavoidable problem. This technology is an algorithm to identify and correct distorted wavefronts in atomic resolution STM images.

A human-in-the-loop machine learning (hML) technology potentially enhances experimental workflows by integrating human expertise with AI automation.

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.