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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Hongbin Sun
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Chad Steed
- Junghoon Chae
- Kyle Kelley
- Prashant Jain
- Travis Humble
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- Anton Ievlev
- Arpan Biswas
- Carter Christopher
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- Debraj De
- Gautam Malviya Thakur
- Gerd Duscher
- Ian Greenquist
- Ilias Belharouak
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- Liz McBride
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Nate See
- Neus Domingo Marimon
- Nithin Panicker
- Olga S Ovchinnikova
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Ruhul Amin
- Sai Mani Prudhvi Valleti
- Samudra Dasgupta
- Stephen Jesse
- Sumner Harris
- Thien D. Nguyen
- Todd Thomas
- Utkarsh Pratiush
- Vishaldeep Sharma
- Vittorio Badalassi
- Xiuling Nie

In nuclear and industrial facilities, fine particles, including radioactive residues—can accumulate on the interior surfaces of ventilation ducts and equipment, posing serious safety and operational risks.

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

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 invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal risks.

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

A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.

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.

The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.

QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.

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