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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Kyle Kelley
- Annetta Burger
- Anton Ievlev
- Arpan Biswas
- Carter Christopher
- Chance C Brown
- Debraj De
- Gautam Malviya Thakur
- Gerd Duscher
- Huixin (anna) Jiang
- James Gaboardi
- Jamieson Brechtl
- Jason Jarnagin
- Jesse McGaha
- Kai Li
- Kashif Nawaz
- Kevin Spakes
- Kevin Sparks
- Liam Collins
- Lilian V Swann
- Liz McBride
- Mahshid Ahmadi-Kalinina
- Mark Provo II
- Marti Checa Nualart
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Rob Root
- Sai Mani Prudhvi Valleti
- Sam Hollifield
- Stephen Jesse
- Sumner Harris
- Todd Thomas
- Utkarsh Pratiush
- Xiaobing Liu
- Xiuling Nie

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 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.

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.

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.

Moisture management accounts for over 40% of the energy used by buildings. As such development of energy efficient and resilient dehumidification technologies are critical to decarbonize the building energy sector.

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.