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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Alex Plotkowski
- Amit Shyam
- Kevin M Roccapriore
- Maxim A Ziatdinov
- James A Haynes
- Kyle Kelley
- Sumit Bahl
- Viswadeep Lebakula
- Alexandre Sorokine
- Alice Perrin
- Andres Marquez Rossy
- Annetta Burger
- Anton Ievlev
- Arpan Biswas
- Carter Christopher
- Chance C Brown
- Clinton Stipek
- Daniel Adams
- Debraj De
- Eve Tsybina
- Gautam Malviya Thakur
- Gerd Duscher
- Gerry Knapp
- James Gaboardi
- Jesse McGaha
- Jessica Moehl
- Jovid Rakhmonov
- Kevin Sparks
- Liam Collins
- Liz McBride
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Neus Domingo Marimon
- Nicholas Richter
- Olga S Ovchinnikova
- Peeyush Nandwana
- Philipe Ambrozio Dias
- Ryan Dehoff
- Sai Mani Prudhvi Valleti
- Stephen Jesse
- Sumner Harris
- Sunyong Kwon
- Taylor Hauser
- Todd Thomas
- Utkarsh Pratiush
- Xiuling Nie
- Ying Yang

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

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.

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

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.

Water heaters and heating, ventilation, and air conditioning (HVAC) systems collectively consume about 58% of home energy use.

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.