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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Sam Hollifield
- Chad Steed
- Junghoon Chae
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- Mingyan Li
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- Anton Ievlev
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- Evin Carter
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- Gerd Duscher
- Harper Jordan
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- Kunal Mondal
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- Mahshid Ahmadi-Kalinina
- Mark Provo II
- Marti Checa Nualart
- Mary A Adkisson
- Mengdawn Cheng
- Nance Ericson
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Oluwafemi Oyedeji
- Oscar Martinez
- Paula Cable-Dunlap
- Raymond Borges Hink
- Rob Root
- Sai Mani Prudhvi Valleti
- Samudra Dasgupta
- Soydan Ozcan
- Srikanth Yoginath
- Stephen Jesse
- Sumner Harris
- T Oesch
- Tyler Smith
- Utkarsh Pratiush
- Varisara Tansakul
- Xianhui Zhao
- Yarom Polsky

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 ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).

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

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

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.

The scanning transmission electron microscope (STEM) provides unprecedented spatial resolution and is critical for many applications, primarily for imaging matter at the atomic and nanoscales and obtaining spectroscopic information at similar length scales.