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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Hongbin Sun
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Kyle Kelley
- Alexandre Sorokine
- Anton Ievlev
- Arpan Biswas
- Clinton Stipek
- Daniel Adams
- Gerd Duscher
- Ilias Belharouak
- Jessica Moehl
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Philipe Ambrozio Dias
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Ruhul Amin
- Sai Mani Prudhvi Valleti
- Stephen Jesse
- Sumner Harris
- Taylor Hauser
- Thien D. Nguyen
- Utkarsh Pratiush
- Vishaldeep Sharma
- Viswadeep Lebakula

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.

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

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modelling building height at scale are hindered by two pervasive issues.

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.

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.

Knowing the state of charge of lithium-ion batteries, used to power applications from electric vehicles to medical diagnostic equipment, is critical for long-term battery operation.

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.