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Florian Bergmann’s research is all about characterizing materials for the next generation of electronic chips. He advances the capabilities of on-wafer microwave-frequency materials characterization techniques and applies them to study functional materials such as ferroelectrics. The goal is optimizing materials performance and uncovering emergent materials properties to enable new chip functionalities.

Jonathan arrived at NIST/¶¶ÒõÂÃÐÐÉä Boulder in late 2024 after completing his PhD in theoretical atomic physics in Australia. Jonathan says he has found his first postdoctoral position both incredibly enriching and at times challenging citing how it’s a completely different field to his background. His primary project has involved developing a cryogenic laser scanning device for absolute energy calibration of transition-edge sensor detectors, which has proved incredibly successful for its direct purpose as well as for related areas of detector characterization and quantum device manipulation. Furthermore, he has been involved with a range of topics from highly-charged ions, antimatter X-rays at CERN, synchrotron studies in Berlin, and continuing his theoretical calculations.

In her role as an associate of the NIST Statistical Engineering Division through ¶¶ÒõÂÃÐÐÉä Boulder PREP, Angela Folz performs statistical analyses for scientists and engineers across NIST, supporting diverse projects such as modeling specimen survivability in atom probe tomography, radio frequency testbed validation, and food safety and ingredient authentication. Her work also includes research on neural network estimators and algorithmic data privacy. Most recently, she is collaborating on advancing statistical methods for high-precision atomic clock evaluation, including comparing methods for quantifying "dark uncertainty" and analyzing the spectral properties of common noise types in clock measurements. This research is necessary to validate assumptions underlying both current and improved statistical methods, essential for the upcoming redefinition of the SI second.

Benedikt Hampel is a Research Associate in the Quantum Nanophotonics / Faint Photonics Group at the National Institute of Standards and Technology (NIST) in Boulder, CO and at the Department of Physics of the University of Colorado Boulder. His research interest focuses on Superconducting Nanowire Single-Photon Detectors (SNSPDs) for applications in quantum computing, astrophysics, and chemistry. He developed wafer-scale fabrication processes in the Boulder Microfabrication Facility (BMF) at NIST to integrate SNSPDs and photonics into ion traps for high-fidelity qubit state readout for scalable quantum computing platforms and characterized ion trap chips at cryogenic temperatures. Furthermore, he contributed to the development of mid-infrared-optimized single-photon cameras for applications in fields like exoplanet spectroscopy and vibrational spectroscopy by demonstrating a 64-pixel mid-infrared SNSPD array and single-photon detection up to 29 µm wavelength.

Erin Maloney is part of the NIST Quantum Electronics Group, where she works on Time Division Multiplexer (TDM) device quality assurance. She qualifies TDM devices for use by collaborators and external researchers. The projects she has qualified devices for cover everything from X-ray detectors to CMB studies to quantum computing. Maloney also provides feedback to the fabrication teams to help improve yield and track issues, when they occur. 

As a part of ¶¶ÒõÂÃÐÐÉä PREP and NIST's Quantum Sensors Division's scientific team, Robinjeet Singh is passionate about applications of Superconducting Quantum Interface Devices (SQUIDs) readout amplifiers to infer signals from TES detector arrays for CMB astronomy, quantum computing, and fast X-ray and Gamma-ray spectroscopy. One of his research efforts is to explore new design and microfabrication techniques for monolithic integration of large arrays of TES detectors to their SQUID readout electronics onto a single wafer. In addition, he is involved in developing techniques for a high-throughput fabrication of SQUID electronics on a larger (150 mm) wafer format. Singh’s above research efforts will enable NIST's future generation of 10 kilo-pixel soft X-ray spectrometers.

Ryan Snodgrass leads the Cryocoolers Team at NIST in Boulder. The team studies the advanced refrigerators that are required to cool a variety of important emerging technologies (including superconducting qubits and detectors) to temperatures close to absolute zero. They are developing new methods to make these refrigerators more accessible and energy efficient, which is important because they set the infrastructure requirements for performing low-temperature science. After making fundamental measurements and analysis, they partner with U.S. industry to commercialize these new technologies and deploy them to users, both academic and industrial.

Dr. Szypryt is a ¶¶ÒõÂÃÐÐÉä PREP Senior Research Associate collaborating with the Quantum Sensors Division at NIST. His research focuses on developing the next generation of quantum calorimeter technologies for applications in quantum information science, nuclear physics, materials science, and astronomy. More recently, he is exploring the kinetic inductance nonlinearity in superconductors as a means of improving the scalability of quantum devices that had previously relied on Josephson junctions. Through his research career, Dr. Szypryt has mentored numerous postdoctoral fellows and graduate students, and he is currently serving on the Applied Superconductivity Conference program committee where he leads the organization of the TES Workshop. 

Nadia Yoza Mitsuishi is a Telecommunications Engineer in the Wireless Coexistence project within the Shared Spectrum Metrology group. Her group studies how the electromagnetic spectrum can be shared more efficiently among wireless technologies, such as 4G, 5G, and Wi-Fi, by developing models, simulations, and measurement methods that characterize how these systems interact and interfere in shared frequency bands. As part of this work, she conducts simulations of wireless coexistence scenarios to optimize performance using various techniques including machine learning and performs physical measurements to evaluate the real-world performance of wireless systems operating in the same frequency bands.